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Data And Analytics Engineer Jobs

15 active opportunities · Updated for September 2026

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Explore current data and analytics engineer jobs. Use filters to narrow by work mode, employment type, experience and date posted.

A
Asana
📍 WarsawFull-time$250K – $360K/yr
1mo ago

The Data Engineering team’s mission is to ensure high-quality data to enable data-informed decision-making across Asana. You will build data artifacts that are leveraged by a wide range of stakeholders in the marketing domain, and create frameworks and tooling used by all data and analytics engineering teams. In this role, you will also partner both with business stakeholders and with the Data Infrastructure team. This role is based in our Warsaw office with an office-centric hybrid schedule. The standard in-office days are Monday, Tuesday, and Thursday. Most Asanas have the option to work from home on Wednesdays. Working from home on Fridays depends on the type of work you do, and your recruiter can share more about the in-office requirements. We offer a Contract of Employment (UoP) for our employees in Poland. What you’ll achieve Design, implement and scale end-to-end data products that support growing data processing and analytical needs. Influence best practices in Databricks and cloud-based data engineering, driving innovation and adoption across teams. Leverage AI to build self-serve tools and accelerate Data/GTM workflows. Establish trust and strong relationships across business and technical teams, ensuring alignment on data strategy and execution. Implement systems that guarantee data quality, governance, and availability. About you 3+ years of hands-on experience in Data Engineering or Software Engineering. Degree in computer science, engineering or equivalent technical field experience. Proficient in cloud-based data processing and storage technologies like Databricks, Spark, Airflow. Fluent in SQL and proficient in at least one modern programming language (e.g., Python, Scala, Java). Proactive self-starter with a proven ability to identify opportunities, propose innovative solutions, and execute them effectively. Excellent communication skills, with the ability to clearly articulate complex technical concepts to non-technical stakeholders. Demonst

pythonjavasql
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GH
greenhouse,Cohere Health
📍 HyderabadFull-time₹2K – ₹2K/yr
12 hrs ago

Opportunity Overview: We are seeking a Sr. Data Engineer to help drive the technical vision of our Data Engineering team as we scale our infrastructure, services, and architecture. This role is ideal for someone who blends deep technical expertise with strategic thinking and cross-functional influence. As a Sr. Data Engineer, you will partner closely with other data and analytics engineers, architects, product leaders, and business stakeholders to evolve our data infrastructure in support of high-trust, scalable, and business-aligned outcomes. You’ll also serve as a force multiplier across teams; raising the bar for data engineering excellence and accelerating the maturity of our data platform capabilities. What you’ll do: Develop, and maintain robust ETL/ELT pipelines to ingest, transform, and load data from multiple source systems into enterprise data platforms. Ensure pipelines are scalable, reusable, fault-tolerant, and optimized for batch and near real-time processing requirements. Develop interactive dashboards, scorecards, and KPI reporting solutions using BI tools. Deliver executive, operational, and analytical reporting aligned with business goals. Identify repetitive manual reporting processes and automate them using scripting, workflow orchestration, scheduling tools, and dashboard refresh mechanisms to improve efficiency, accuracy, and turnaround time. Collaborate with internal stakeholders and leadership teams to understand data integration and reporting needs, define KPIs, document business rules, and translate requirements into scalable technical solutions. Implement data validation checks, reconciliation controls, lineage documentation, metadata standards, and governance policies to maintain trusted, secure, and compliant data assets across the organization. Provide technical guidance, code reviews, best practices, and mentor junior team members. Investigate and resolve production incidents related to pipelines, delayed reports, data mismatches

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Vanta
📍 United StatesFull-time
1mo ago

At Vanta, our mission is to help businesses earn and prove trust. We believe that security should be monitored and verified continuously, and we empower companies to practice better security and prove it with ease. Vanta has a kind and talented team, and while some have prior security experience, many have been successful at Vanta without it. Our Data and Analytics team is currently looking for a Senior Data Scientist to join us! You’ll be responsible for laying the foundation for a best-in-class business analytics function. You’ll partner closely with our business stakeholders to ensure that our analytics stack and processes meet the business needs today with an eye towards the future. What you’ll do as a Senior Data Scientist at Vanta: Build and maintain trusted product data assets using dbt, Snowflake, and modern analytics infrastructure Leverage AI-powered analytics tools and data agents (e.g., Snowflake Cortex) to accelerate insight generation, automate repeatable analysis, and scale decision-making Define and evolve measurement frameworks for product health, customer lifecycle, and AI-powered product experiences Partner closely with Product, Engineering, Design, and Customer Success to influence product strategy through data Help define Vanta’s analytics strategy and AI measurement practices as our product and data platform evolve Lead executive analytics reviews, translating complex analyses into clear recommendations that drive company decisions How to be successful in this role: 4+ years of experience working with data as a Data Scientist, Product Analyst, or Analytics Engineer in an applied business setting Strong foundation in SQL, Python (or R), statistics, and machine learning Experience designing and evaluating experiments, predictive models, and other statistical analyses to inform product decisions Experience building scalable data assets, metrics, and analytical frameworks on modern cloud data platforms (e.g., Snowflake, dbt) Deep experience with da

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Gitlab
📍 United StatesFull-timeRemote
1mo ago

GitLab is the intelligent orchestration platform for DevSecOps. GitLab enables organizations to increase developer productivity, improve operational efficiency, reduce security and compliance risk, and accelerate digital transformation. More than 50 million registered users and more than 50% of the Fortune 100* trust GitLab to ship better, more secure software faster. The same principles built into our products are reflected in how our team works: we embrace AI as a core productivity multiplier, with all team members expected to incorporate AI into their daily workflows to drive efficiency, innovation, and impact. GitLab is where careers accelerate, innovation flourishes, and every voice is valued. Our high-performance culture is driven by our values and continuous knowledge exchange, enabling our team members to reach their full potential while collaborating with industry leaders to solve complex problems. Co-create the future with us as we build technology that transforms how the world develops software. * Fortune 500® is a registered trademark of Fortune Media IP Limited, used under license. Claim based on GitLab data. Fortune 100 refers to the top 20% ranked companies in the 2025 Fortune 500 list, published in June 2025. Fortune and Fortune Media IP Limited are not affiliated with, and do not endorse products or services of GitLab. An Overview of This Role GitLab is seeking a VP of Data and Insights to lead the strategic vision, architecture, and execution of our enterprise data platform and analytics capabilities. Reporting to the CIO, you'll oversee a distributed team spanning data platform and engineering, analytics engineering, data governance, and data analysts embedded across business functions. This role represents a transformational opportunity to move GitLab beyond traditional dashboard development toward a truly AI-enabled, self-service data organization where stakeholders access insights on demand and data analysts focus on high-value strategic w

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OpenAI
📍 San FranciscoFull-time
1mo ago

About the Team The IT and Security organization builds the systems, data foundations, and automation that help OpenAI operate securely and reliably at scale. We support critical domains across identity, access, infrastructure security, enterprise systems, and internal productivity. As OpenAI grows, audit readiness and control assurance increasingly depend on reliable data: accurate system inventories, access populations, change records, configuration state, exception signals, and evidence generated directly from source systems. Our goal is to move beyond manual evidence collection and build scalable data products, automated validation, and continuous control monitoring that make security and IT controls measurable, repeatable, and defensible. About the Role We are looking for an IT Controls Data Engineer to build the data infrastructure that powers audit readiness, IT controls, evidence automation, and continuous control monitoring. In this role, you will design and maintain the pipelines, datasets, models, validation logic, dashboards, and evidence exports that make IT controls measurable, repeatable, and defensible. You will work across Security, IT, Infrastructure, Engineering, Finance Risk Management, and auditors to turn complex system behavior into reliable control data products. This is a technical builder role. The ideal candidate is strong in data engineering and analytics engineering, comfortable working with enterprise and security system data, and able to explain data lineage, source-system behavior, and control logic clearly to technical and audit stakeholders. You’ll be responsible for Building reliable data pipelines, models, and datasets for IT controls, including access, identity, configuration, change, ticketing, exception, and evidence data. Creating data quality, lineage, reconciliation, and completeness checks that make control data defensible for SOX and other audit use cases. Designing automated evidence generation workflows that produce compl

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T
Twilio
📍 - USFull-timeRemoteFrom $141.5K/yr
1mo ago

Who we are At Twilio, we’re shaping the future of communications, all from the comfort of our homes. We deliver innovative solutions to hundreds of thousands of businesses and empower millions of developers worldwide to craft personalized customer experiences. Our dedication to remote-first work , and strong culture of connection and global inclusion means that no matter your location, you’re part of a vibrant team with diverse experiences making a global impact each day. As we continue to revolutionize how the world interacts, we’re acquiring new skills and experiences that make work feel truly rewarding. Your career at Twilio is in your hands. . Hiring and how we work We use Artificial Intelligence (AI) to help make our hiring process efficient. That said, every hiring decision is made by real Twilions! Also, while we are a remote-first company, you may be asked to report in person on an ad-hoc basis for team gatherings, functional off-sites or customer meetings. . See yourself at Twilio Join the team as Twilio’s next Sr. Analytics Engineer, R&D. About the job This position is needed to advance the consistency & quality of our R&D analytics data layer and accelerate the development velocity of analysts. Our Data Science and Analytics team seeks to empower R&D to make data-backed decisions that accelerate innovation and improve product performance. You will work closely within our team and across Product & Engineering to design and maintain a robust analytics data layer that enables trusted reporting on R&D metrics. Responsibilities In this role, you’ll: Design and implement a formal analytics data layer using AWS Glue, Athena / Presto, and LookML Collaborate within the Data Science & Analytics team and across Product & Engineering to define, document, and maintain alignment on metric definition and data lineage Develop and maintain automated data reconciliation and quality checks to

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Mixpanel
📍 United StatesFull-timeFrom $273K/yr
1mo ago

About Mixpanel Mixpanel is the leading product intelligence and analytics platform, trusted by more than 29,000 companies to help understand how people use the products they build. By combining powerful analytics with AI that knows your business, Mixpanel helps teams see what’s working, diagnose what’s not, and decide what to build next. Learn more at mixpanel.com . About the Team Internal Analysis is the data team at Mixpanel — the team that turns data from every corner of the business into the decisions that shape our product and our growth. They own the full path: from raw data in source systems, through a governed warehouse, to the models, metrics, and insights leaders across the company act on. It's two complementary disciplines under one roof. Our Analytics Engineers own the data end to end — ingesting from source systems, modeling through a medallion architecture on BigQuery, and producing the trusted tables and reporting artifacts the rest of the company runs on. Our Data Scientists build on that foundation, partnering with Product to refine the user experience and with GTM to sharpen how we grow — inspecting signals, running experiments, and surfacing the insights that change what we do next. About the Role You'll lead this team — and help shape Mixpanel's data culture. We're looking for someone who can influence the organization to become more metrics-driven: establishing clear KPIs, helping teams define success upfront, and ensuring analytics and data science are engaged as strategic partners from the start of an initiative, not brought in at the end to validate decisions already made. As we grow the data organization's remit across the company, this role has the scope to establish practices that don't yet exist, KPI ownership, cross-functional operating rhythms, a shared standard for what 'data-driven' means here, and where AI belongs in both how the team works and what the platform delivers. It takes building real trust with cross-functional leaders to

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For over 20 years, Smartsheet has empowered teams to manage work seamlessly and scale solutions smarter. Now, in our most ambitious chapter yet, we are uniting human teams with AI agents. By orchestrating the work agents do best, automating manual tasks and uncovering insights at scale, we create the space for people to focus on what truly matters: judgment, creativity, and big thinking. That is magic at work, and it’s what we show up for every day. Smartsheet is hiring a Senior Analytics Engineer to lead the way in data-driven decision-making. You will be responsible for the creation and maintenance of a governed, reliable, and scalable analytics system, transforming raw data into usable datasets for DS/ML, analytics, and reporting. A key aspect of this role is leading the architecture and implementation of efficient data transformation systems within Snowflake, fostering data democratization and impacting business outcomes. Working closely with BI analysts and Data scientists, you will ensure data accessibility and drive activation on critical customer-facing platforms. This full-time position reports to the Director of Analytics Engineering and is based in Smartsheet’s corporate offices in Bengaluru, India. You Will: Leading the implementation of efficient and scalable systems that optimize data transformations from our data lake in Snowflake into clean, documented data products. Contribute to the design standards and architectural principle standards, designs and processes. Build and maintain a governed, robust, reliable, and scalable analytics system (DW/DV). Collaborating with BI analysts and data scientists to provide proper data accessibility guidelines. Foster data democratization via activation of data on critical platforms like Smartsheet platform, Amplitude, Thoughtspot , Gainsight. Create and contribute to frameworks that improve data quality and observability to identify and resolve issues faster. Create and implement data testing plans, en

sqlawsci/cd
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T
Twilio
📍 - USFull-timeRemote$155.5K – $194.4K/yr
1mo ago

Who we are At Twilio, we’re shaping the future of communications, all from the comfort of our homes. We deliver innovative solutions to hundreds of thousands of businesses and empower millions of developers worldwide to craft personalized customer experiences. Our dedication to remote-first work , and strong culture of connection and global inclusion means that no matter your location, you’re part of a vibrant team with diverse experiences making a global impact each day. As we continue to revolutionize how the world interacts, we’re acquiring new skills and experiences that make work feel truly rewarding. Your career at Twilio is in your hands. . Hiring and how we work We use Artificial Intelligence (AI) to help make our hiring process efficient. That said, every hiring decision is made by real Twilions! Also, while we are a remote-first company, you may be asked to report in person on an ad-hoc basis for team gatherings, functional off-sites or customer meetings. . See yourself at Twilio Join the team as Twilio’s next Staff, Analytics Engineer, GTM Data Science & Analytics. About the job This position is needed to advance the quality, reliability, and strategic value of Twilio’s Go-To-Market (GTM) data by designing and maintaining a robust business data layer to enable trusted sales analytics, reporting, data science, & AI capabilities. The Staff, Analytics Engineer will play a mission-critical role in driving cross-functional alignment within GTM Data Science & Analytics and Sales Operations on key Sales & Finance business metrics, ensuring data consistency and empowering data-driven decision-making. Responsibilities In this role, you’ll: Design and implement a formal business data layer in dbt, ensuring that data from multiple sources is centralized, reconciled, and serves as a single source of truth for GTM metrics. Collaborate with stakeholders within the GTM Operations team and Finance to define, document, and mai

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S
1mo ago

At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done. About Snowflake Snowflake started with a clear vision: develop a cloud data platform that is effective, affordable, and accessible to all data users. Snowflake developed an innovative new product with a built-for-the-cloud architecture that combines the power of data warehousing, the flexibility of big data platforms, and the elasticity of the cloud at a fraction of the cost of traditional solutions. We are now a global, world-class organization with offices in more than a dozen countries and serving many more. This role requires in-person attendance in our Pune office at least 3 days per week. Job Description We are looking for an Analytics Engineer to join our growing Finance Analytics Engineering team. In this role, you will drive value and empower decision-making by developing and maintaining the data infrastructure which fuels reporting and analysis for the Finance organization and has a direct impact on Snowflake’s success as a company. As an Analytics Engineer, you will be responsible for the following: Use SQL, Python, Snowflake, dbt, Airflow, and other systems while working within an agile development model to build and maintain data infrastructure for use in reporting, analysis, and automation Perform data QA and develop automated testing procedures for use with S

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P
9 hrs ago

About Us Pearl is AI for professional services at global scale, combining advanced AI with verified human expertise to deliver help that is accurate, accountable, and fast. Since 2003, our network has connected millions of customers with licensed professionals across 196 countries, making real expertise available anytime, anywhere. Our Values Data driven: Start with truth, measure what matters. Courageous: Bias to action; run toward hard problems. Innovative: Seek novel, elegant solutions. Lean: Do more with less. Build, ship, learn fast. Humble: Strong opinions, lightly held. About the Role The future of analytics isn't dashboards. It's intelligent systems that anticipate questions, surface insights, and help people make better decisions. We're looking for a Senior Analytics Engineer to help build that future at Pearl. In this role, you'll design and develop AI-powered analytics experiences that combine trusted enterprise data with modern AI capabilities, enabling business users to interact with data conversationally and uncover insights faster than ever before. You'll build production AI agents, create scalable semantic data models, develop intelligent analytics applications, and establish best practices for responsible AI across the Analytics organization. Working closely with Product, Engineering, and business leaders, you'll turn emerging AI technologies into real business capabilities that improve decision making across the company. This is an opportunity to help define how AI transforms analytics at Pearl while working on some of the most exciting technologies in data, LLMs, and agentic AI. What You’ll Do Build proactive analytics and AI solutions that surface actionable business insights, anticipate business needs, and enable smarter decision-making. Design and develop AI-powered analytics tools, including conversational interfaces that allow business users to query data using natural language. Build semantic data models and reusab

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Vanta
📍 United StatesFull-time
1mo ago

At Vanta, our mission is to help businesses earn and prove trust. We believe that security should be monitored and verified continuously, and we empower companies to practice better security and prove it with ease. Vanta has a kind and talented team, and while some have prior security experience, many have been successful at Vanta without it. As a Senior Analytics Engineer, you’ll be responsible for laying the foundation for a best-in-class analytics function. You’ll partner closely with our data science team and business stakeholders to ensure that our analytics stack and processes meet the business needs today with an eye towards the future. What you’ll do as an Senior Analytics Engineer at Vanta: Design and implement complex data models to enable dashboards, self-serve analytics, and data science teams. Write highly tuned, scalable SQL queries running over large-scale, heterogeneous data warehouses. Enable AI tooling with semantic layers and observability, guiding analytics functions on best practices. Manage and improve data infrastructure needed to drive data-driven decision-making solutions. Help develop front end applications to expose analytical data sets enterprise wide Work with the Product and Corporate Engineering system teams to structure source systems for reporting consumption across the enterprise. How to be successful in this role: Have at least four years of experience working with data and two years of experience in Software Engineering or a related field. Have experience with common analytics tooling (e.g. dbt is a must, Stitch/Fivetran, Snowflake/BigQuery/Redshift, Airflow, Dagster, Looker/Mode/Sigma). Bring a system-oriented and software engineering mindset to the Analytics Engineering practice. We’re looking to build frameworks that manage data, and minimize bespoke queries. Deep knowledge of crafting dimensional and fact models in modern data fashion. Have a passion for enabling the developer experience of data, and being obsessed with giving

sqlrestai
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Clickup
📍 United StatesFull-time
1mo ago

At ClickUp, we're building the future of work: the first truly converged AI workspace unifying tasks, docs, chat, calendar, and enterprise search, all supercharged by context-driven AI. We are an AI-native company. Every team member is expected to leverage AI daily, and we evaluate AI fluency as part of our hiring process. Join us and help redefine what's possible. 🚀 We're looking for a Staff Data Engineer to own the architecture and technical vision of our data platform. This is a high-leverage, high-autonomy role where you'll set the technical bar for the team, drive cross-functional alignment on data infrastructure strategy, and solve our hardest engineering problems. You'll operate across AWS serverless technologies, Snowflake, dbt, and Terraform, but your impact goes well beyond any single tool: you'll shape how we think about reliability, scalability, cost, and developer experience at the platform level. This role is for someone who doesn't just build great systems, but makes the engineers around them better. The Role: Own the technical architecture of ClickUp's data platform, making design decisions that balance scalability, cost, reliability, and velocity. Define and drive the technical roadmap for data infrastructure in partnership with leadership. Design systems at scale : build frameworks, abstractions, and patterns that other engineers use daily. Lead complex, cross-team technical initiatives spanning data engineering, analytics engineering, data science, and data analytics. Drive cost optimization across cloud infrastructure and compute, turning efficiency into a competitive advantage. Build and evolve our data pipelines using AWS serverless (Lambda, Fargate, Step Functions, Kinesis, S3, DynamoDB, Aurora), Snowflake, and dbt. Establish and champion engineering standards : observability, testing, CI/CD, code review, and documentation practices. Design and maintain infrastructure for AI/ML workloads , including LLM frameworks, feature pipelines, training

pythonsqlaws
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Snowflake
📍 Menlo ParkFull-time
1mo ago

At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done. Our Data Analytics and AI org (DAA) is actively seeking a Staff Analyst, GTM Analytics to contribute to building our framework to identify opportunities for new logo acquisition and core customer expansion. Examples of deliverables include agentic campaign activation platform, architecting intelligent data foundations, and diving into core org metrics such as ROI and funnel leakage. This is a hybrid (3 days in office) role in Menlo Park IN THIS ROLE YOU WILL: Be a Strategic Partner to Leadership: Partner with Marketing executives to align analytics initiatives with global business objectives — active GTM alignment, technical roadmap strategy, shaping investment decisions, and proactively surfacing insights that move the business, not just inform it. Turn Data into Business Outcomes: Go beyond reporting to influence pipeline generation, conversion optimization, and campaign ROI — presenting complex analytical findings to the team with clarity and impact. You measure success by decisions changed, not dashboards shipped. Master the Analytical Foundation: Maintain deep fluency in the data models, metrics, and pipelines (SQL, dbt, Snowflake) that power GTM reporting. Partner closely with Analytics Engineering and Data Engineering teams to ensure insights are accurately surfaced

pythonsqlrest
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OpenAI
📍 San FranciscoFull-time
1mo ago

About the Team The GTM Intelligence Solutions team builds the data and decision systems that help customer-facing teams take the right action at the right time. We combine product telemetry, commercial data, customer context, and field activity to identify account health and opportunity, recommend actions and use cases, deliver intelligence through field-facing products and agent workflows, and measure what happens next. We’re looking for a Data Scientist to help build the next generation of GTM intelligence at OpenAI. You will own a flexible portfolio of high-impact decision data products and work closely with Technical Success and other GTM teams to ensure the work drives better decisions. About the Role As a Data Scientist on GTM Intelligence Solutions, you will define and build the intelligence systems that help customer-facing teams prioritize accounts, identify risks and opportunities, choose interventions, and understand what worked. You will set the roadmap and methodology, build canonical features, ship reliable production workflows, monitor quality and adoption, and improve the systems using field feedback and business outcomes. This role combines hands-on technical depth with strong product and business judgment. You should be as comfortable writing production Python and advanced SQL, defining durable data contracts, and operating decision products as you are evaluating a ranking approach or designing an experiment. You will personally ship reliable first versions and partner with Analytics Engineering and Data Engineering when work requires shared infrastructure or additional scale. In This Role, You Will Set the roadmap and methodology for GTM intelligence and decision products, using deep stakeholder discovery to probe beyond stated requests, uncover the underlying decisions, workflows, constraints, and measures of success, and translate them into measurable systems. Own the full lifecycle of intelligence products, including feature definition, methodo

pythonsqlaws
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