Data Modelling Consultant Jobs

About the Role The Data Platform team owns the end-to-end data lifecycle at Perplexity, from ingestion through processing, storage, and serving, powering product features, analytics, experimentation, AI workloads, and the company’s data lake. The team defines the architecture for batch and streaming systems, the orchestration and observability stack, and a self-serve data platform, while thoughtfully combining platforms such as Databricks and Snowflake with open-source technologies including Spark, Kafka, Flink, Airflow, Dagster, dbt, Iceberg, Delta Lake, and ClickHouse. In this senior/staff role, you will shape architecture, set standards, and drive the long-term technical direction of Perplexity’s data ecosystem. Key Responsibilities Design and operate large-scale batch and streaming data pipelines that directly power Perplexity product features, AI training and evaluation workflows, analytics, and experimentation. Build event-driven and streaming systems (Kafka, Kinesis, PubSub, or similar) for real-time ingestion, transformation, and delivery, alongside batch frameworks for backfills, aggregations, and offline computation. Lead the architecture of data orchestration using tools like Airflow or Dagster, owning scheduling, dependency management, retries, SLAs, and end-to-end observability for critical data flows. Set and enforce guarantees for data correctness, freshness, lineage, and recoverability, designing systems that handle rapid scale growth, partial failures, and evolving schemas without disrupting AI workloads or product experiences. Build self-serve data platforms that let engineers, data scientists, and analysts safely discover data, define contracts, and create and operate their own pipelines with minimal friction. Improve developer experience through better abstractions, opinionated paved paths, and standards for data modeling, testing, validation, and deployment, treating the data platform as a product used by many teams. Drive architectural decision

Our vision is to transform how the world uses information to enrich life for all . Micron Technology is a world leader in innovating memory and storage solutions that accelerate the transformation of information into intelligence, inspiring the world to learn, communicate and advance faster than ever. Design, build, and maintain scalable, reliable, and high-availability data platforms and data pipelines to support analytics and data-driven applications Collaborate closely with data scientists, analysts, product teams, and software engineers to translate business requirements into robust and reusable data solutions Own data modeling and data architecture design to ensure data consistency, accuracy, and long-term maintainability Develop and optimize both batch and real-time (streaming) data processing pipelines to improve performance and system stability Ensure data quality, data governance, and data security through monitoring, validation, and anomaly detection mechanisms Continuously improve existing data pipelines and platforms through performance tuning, cost optimization, and technical debt reduction Participate in technology selection for data platforms and tools (e.g., databases, cloud services, data processing frameworks) and promote engineering best practices Create and maintain technical documentation to support knowledge sharing and long-term system sustainability Mentor and support junior data engineers, contributing to the overall technical growth and engineering excellence of the team Stay current with emerging trends and technologies in data engineering and big data, and evaluate their potential adoption and business value Responsibilities include, but not limited to: <span

Omada Health is on a mission to bend the curve of chronic disease. Job overview: We are dedicated to leveraging data to drive strategic decision-making and operational efficiency. Our team is passionate about harnessing the power of data to solve complex problems and deliver impactful insights. We are seeking a highly skilled and motivated Data Engineer to join our team. The ideal candidate will be responsible for designing, building, and maintaining robust data architectures and engineering data models and pipelines. This role will play a critical part in ensuring the integrity, scalability, and performance of our data processing and products. Key Responsibilities: Data Architecture: Design, develop, and implement scalable, secure, and efficient data solutions that meet the needs of the organization. Data Modeling: Create and maintain logical and physical data models to support business intelligence, analytics, and reporting requirements. Pipeline Engineering: Design, build, and optimize ETL (Extract, Transform, Load) processes and data pipelines to ensure smooth and efficient data flow from various sources. Data Integration: Integrate diverse data sources, including APIs, databases, and third-party data, into a unified data platform. Performance Optimization: Monitor and optimize the performance of data systems and pipelines to ensure low latency and high throughput. Data Quality and Governance: Implement data quality checks, validation processes, and governance frameworks to ensure the accuracy and reliability of data. Collaboration: Partner closely with data scientists, analysts, and other stakeholders to understand data requirements and deliver solutions that meet their needs. Documentation: Maintain comprehensive documentation of data architectures, models, and pipelines for ongoing maintenance and knowledge sharing. Training: You'll train and collaborate with teammates effectively in data engineering best practices Technical Influence/Leadership: Recommends p

About the position Showpad is building a Revenue Intelligence engine that transforms raw signals—CRM data, email threads, transcripts, and content engagement—into prescriptive AI guidance. We are looking for a technical Product Manager to own the unified data intelligence layer that powers this engine. You will define how we capture and model data, and critically, determine the best retrieval and inference strategies (Search, RAG, Knowledge Graphs, or Vector Similarity) for every use case. Key Responsibilities Data Modeling & Architecture : Define the canonical model for entities (deals, contacts, skills) and establish the retrieval strategy—choosing between keyword, dense vector, hybrid, or graph traversal based on latency and accuracy. Search & RAG Ownership : Own the end-to-end RAG pipeline (chunking, embeddings, indexing). Write technical specs for retrieval layers in Meeting Prep and Roleplay AI, and define evaluation metrics (Recall@k, MRR). Revenue Intelligence Roadmap : Drive the vision from "trusted foundation" to "prescriptive AI." Own the product logic for Deal Health and Winning Behavior models. Platform Enablement : Act as the internal PM champion for the data platform, providing semantic primitives, event taxonomies, and data contracts to other product squads. Discovery & Strategy : Conduct deep customer discovery and stay ahead of LLM/Search trends, translating fuzzy business questions into scoped ML problems. Required Skills Must haves 5+ years in PM: at least 2 years specifically owning data platforms, search, analytics, or ML products. Retrieval Expertise: Hands-on experience shipping RAG pipelines or search systems. You understand the trade-offs between BM25, vector search, and reranking. Data Technicality : Fluency with Datalake architectures (Delta Lake, BigQuery, etc.) and strong entity-relationship modeling skills. ML Fluency : Ability to define features, label designs, and evaluation metrics. You can review a technic

About the position Showpad is building a Revenue Intelligence engine that transforms raw signals—CRM data, email threads, transcripts, and content engagement—into prescriptive AI guidance. We are looking for a technical Product Manager to own the unified data intelligence layer that powers this engine. You will define how we capture and model data, and critically, determine the best retrieval and inference strategies (Search, RAG, Knowledge Graphs, or Vector Similarity) for every use case. Key Responsibilities Data Modeling & Architecture : Define the canonical model for entities (deals, contacts, skills) and establish the retrieval strategy—choosing between keyword, dense vector, hybrid, or graph traversal based on latency and accuracy. Search & RAG Ownership : Own the end-to-end RAG pipeline (chunking, embeddings, indexing). Write technical specs for retrieval layers in Meeting Prep and Roleplay AI, and define evaluation metrics (Recall@k, MRR). Revenue Intelligence Roadmap : Drive the vision from "trusted foundation" to "prescriptive AI." Own the product logic for Deal Health and Winning Behavior models. Platform Enablement : Act as the internal PM champion for the data platform, providing semantic primitives, event taxonomies, and data contracts to other product squads. Discovery & Strategy : Conduct deep customer discovery and stay ahead of LLM/Search trends, translating fuzzy business questions into scoped ML problems. Required Skills Must haves 5+ years in PM: at least 2 years specifically owning data platforms, search, analytics, or ML products. Retrieval Expertise: Hands-on experience shipping RAG pipelines or search systems. You understand the trade-offs between BM25, vector search, and reranking. Data Technicality : Fluency with Datalake architectures (Delta Lake, BigQuery, etc.) and strong entity-relationship modeling skills. ML Fluency : Ability to define features, label designs, and evaluation metrics. You can review a technic

Who We Are At OKX, we believe that the future will be reshaped by crypto, and ultimately contribute to every individual's freedom. OKX is a leading crypto exchange, and the developer of OKX Wallet, giving millions access to crypto trading and decentralized crypto applications (dApps). OKX is also a trusted brand by hundreds of large institutions seeking access to crypto markets. We are safe and reliable, backed by our Proof of Reserves. Across our multiple offices globally, we are united by our core principles: We Before Me , Do the Right Thing , and Get Things Done . These shared values drive our culture, shape our processes, and foster a friendly, rewarding, and diverse environment for every OK-er. OKX is part of OKG, a group that brings the value of Blockchain to users around the world, through our leading products OKX, OKX Wallet, OKLink and more. About the Opportunity OKX Data Team is responsible for the whole data scope of OKG, from techincal selection, architecture design, data ingestion, data storage, ETL, data visualization to business intelligence and data science. We are data engineers, data analysts and data scientists. The team has end-to-end ownership of most of the data at OKx throughout the whole data lifecycle including data ingestion, data ETL, data warehouse and data services. As a Product Manager of the team, you will work with the team to leverage data technologies to empower evidence-based decision-making and improve the quality of the company's products and services. What You’ll Be Doing Deeply understand business goals and pain points : Work closely with business teams to understand their day-to-day data needs, identify core metric frameworks and key insight opportunities, and proactively propose data-driven solutions. End-to-end data solution design : Translate business requirements into data requirements, owning the full lifecycle from event tracking design, data modeling, and metric definition to dashboard

Scale AI is seeking a highly skilled and motivated AI Data Engineer to join our dynamic Federal Engineering team. As a part of this team, you will play a critical role in supporting Scale’s government customers by scoping and developing onsite solutions. Our scalable, high-performance platform is the foundation for these customer solutions, and your expertise will be instrumental in designing and implementing systems that can handle interactions with existing customer systems to help our products integrate into existing customer workflows. You will: Be open to >50% onsite work in a secured space. Collaborate with cross-functional teams to define and execute the vision for data pipelines and agents. Implement end-to-end data integrations, syncing customer’s data to Scale’s platform and back. Deploy and maintain Scale software at customer sites. Develop customer requested features and work closely with them to ensure that they win customer love. Build robust and reliable backend systems that can serve as standalone products, empowering customers to accelerate their own AI ambitions. Participate actively in customer engagements, working closely with stakeholders to understand requirements and deliver innovative solutions. This role will require at minimum an active Secret clearance and willingness to obtain a TS/SCI security clearance. Ideally you have: Data Engineering: Knowledge of ETL (Extract, Transform, Load) processes and experience in building data pipelines to integrate and process diverse data sources. Understanding of data modeling, data warehousing, and data governance principles Track record of success as a hybrid customer facing engineer, forward deployed software engineer, and ability to quickly adapt to different roles. Prior experience developing with Python Cloud-Native Technologies: Familiarity with cloud platforms (e.g., AWS, Azure, GCP) and experience in developing and deploying applications in a cloud-native environment. Unders

About the Role As a member of the Data team within the Go-to-Market organization, you will help build a data-driven culture, improve decision-making, and advance strategic initiatives through analytics. This is a full-stack data role spanning data modeling, metric definition, visualization, analysis, and self-service tooling. You will build trusted, scalable data sources and products that give the business reliable, actionable insights. The work calls for judgment: you will choose the tool, approach, and level of investment that best fit each problem, from a focused analysis to a durable production data product. As a core partner to the GTM organization, you will address both foundational and ad hoc analytics needs. You will turn complex data into clear narratives that help technical and non-technical audiences understand what is happening, why it matters, and what they should do next. In This Role, You Will Partner closely with GTM teams to proactively identify high-impact questions and translate business needs into data models, metrics, analyses, and scalable technical solutions. Define, source, validate, and operationalize the metrics that guide the business, helping teams incorporate them into planning and day-to-day decisions. Lead cross-functional data projects across established and emerging business areas, including setting the data strategy for greenfield domains. Build scalable data models and pipelines that integrate and transform data from multiple sources into trusted, accessible datasets. Create dashboards, reports, analytical tools, and other data products that enable stakeholders to answer questions independently. Own the lifecycle of metrics, analytical models, and data products from initial exploration and prototyping through production and ongoing maintenance. Choose the most effective approach for each problem—whether an analysis, metric, data model, visualization, or self-service product—based on the audience, urgency, complexity, and expected v

Opportunity Overview: We are seeking a Sr Business Intelligence Engineer to join our Intelligence team. In this role, you will drive the development and optimization of our analytical infrastructure, enabling efficient, scalable, and consistent reporting and analytics across the organization. You will play a critical role in shaping the foundation of our BI ecosystem—working at the intersection of engineering, data modeling, and stakeholder enablement. This is an ideal opportunity for an experienced BI engineer who can execute cross-functional projects, design performant data models, and contribute to the execution of a unified data strategy across platforms. You will also provide guidance and mentorship to junior team members and contribute to the evolution of Cohere’s modern data stack and governance practices. What you’ll do: Lead the execution and refinement of our business intelligence and analytics architecture, ensuring consistency, performance, and scalability across dashboards and self-service tools. Design and implement robust semantic and dimensional data models supporting operational, clinical, and strategic analytics use cases. Collaborate closely with data platform, analytics, and product teams to define shared data definitions, build source-of-truth datasets, and align transformations with stakeholder needs. Improve data pipeline efficiency and maintainability by establishing and enforcing best practices in dbt modeling, testing, and documentation. Support release management, quality testing, version control, and promotion of analytics assets across environments. Enable data providers and analysts to deliver high-impact dashboards and KPI frameworks using Tableau, with an emphasis on performance, usability, and governance. Serve as the primary Tableau Cloud SME for the organization, including user management, security, performance tuning, and environment configuration. Lead integration of Tableau dashboards into front-end web applications using the Ta

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. We’re looking for a Manager/ Sr. Manager to lead Finance Analytics—redefining how Finance leverages data, automation, and AI to operate at scale. This role sits at the intersection of analytics engineering, data product development, and applied AI, and is responsible for building both the team and the systems that power next-generation Finance. You won’t just deliver dashboards—you’ll lead the development of scalable data products, intelligent workflows, and AI-driven applications that transform how Finance operates, makes decisions, and drives efficiency. This is a highly cross-functional leadership role requiring a balance of strategy, execution, and people leadership. You’ll partner closely with Finance, business stakeholders, and Engineering to translate ambiguity into durable, production-grade solutions. In this role, you will: Set vision and lead execution Define and drive the roadmap for Finance Analytics, aligned to business priorities and long-term data strategy. Translate ambiguous business problems into scalable data products, AI solutions, and automation initiatives. Build and lead a high-performing team Hire, develop, and mentor a team of analysts, analytics engineers, and data product builders. Establish best practices across data modeling, experimentation, an

Spaulding Ridge is an advisory and IT implementation firm. We help global organizations get financial clarity into the complex, daily sales, and operational decisions that impact profitable revenue generations, efficient operational performance, and reliable financial management. At Spaulding Ridge, we believe all business is personal. Core to our values is our relationships with our clients, our business partners, our team, and the global community. Our employees dedicate their time to helping our clients transform their business, from strategy through implementation and business transformation. What You Will Do and Learn As a Snowflake Architect in Data Solutions, you'll lead pre-sales, estimation, scoping, design, and delivery of modern analytics solutions on Snowflake. You'll act as a hands-on architect and delivery lead on your own projects, while also providing technical guidance and people leadership to team members deployed across multiple client engagements. Architecture & Delivery Own end-to-end Snowflake solution architecture: data modeling, warehouse sizing and cost optimization, RBAC/security design, data sharing, and performance tuning Lead the data engineering lifecycle - research, POCs, architecture, design, development, testing, deployment, and maintenance Design and build POCs for modern analytics stacks across cloud-based business systems for prospective clients Translate client business needs into technical solution designs and actionable recommendations for platform, structural, or logic issues Manage day-to-day technical relationship with client stakeholders on active engagements Pre-Sales Lead technical workstreams in pre-sales: estimation, scoping, solution proposals, and orals/proposal defense sessions Partner with other practices on cross-functional solution plays and pre-sales activity Support sales cycles by leading solution presentations and building POCs for prospective clients People & Team Leadership Manage, mentor, and

Ready to do the most impactful work of your career? At Coinbase , we are uncompromising on our mission to increase economic freedom. The bar is high, the environment is intense, and we like it that way. This isn't a place for complacency, it’s a place to be pushed past your perceived limits. If you're ready to build the future of finance alongside people who refuse to settle for "good enough," you belong here. Coinbase is a remote-first, but not remote-only company. Expect to get together quarterly for intense in-person working sessions called “surges.” learn more about working at Coinbase . Senior Analytics Engineer As a Senior Analytics Engineer on the Platform team, you'll build the scalable data models and pipelines that power analytics, experimentation, and decision-making across Coinbase. Our Analytics Engineering team transforms raw data into trusted, well-modeled sources that stakeholders across Product, Engineering, and Data Science rely on daily. You'll own end-to-end data solutions for specific business domains, turning complex data flows into clean, reusable frameworks that unlock commercial value at scale. What you'll do: Own end-to-end data modeling for assigned business domains, from understanding source system data flows through designing modular, reusable models (star/snowflake schemas) that serve as the single source of truth for downstream teams. Build and optimize ETL/ELT pipelines using modern tools like dbt and Airflow, ensuring data quality, reliability, and performance at scale across Snowflake or similar warehouse architectures. Partner with Engineering, Product, and Data Science teams to identify data gaps, define requirements, and deliver data products that directly enable experimentation, ad hoc analysis, and business metric optimization. Develop scalable abstractions and frameworks (UDFs, Python packages, internal data apps) that multiply the efficiency of other data teams and reduce time-to-insight across the organization. D

We offer a hybrid work environment. Most US-based positions can also be performed remotely (any exceptions will be noted in the Minimum Qualifications below.) Our Mission: To actively connect people to their next great opportunity. Who We Are: ZipRecruiter is a leading online employment marketplace. Powered by AI-driven smart matching technology, the company actively connects millions of all-sized businesses and job seekers through innovative mobile, web, and email services, as well as through partnerships with the best job boards on the web. ZipRecruiter has the #1 rated job search app on iOS & Android. Summary : As a BI Engineer II on our Business Intelligence team, you'll sit at the intersection of data, business, and engineering — designing the data systems, models, and AI-powered tooling that scale how ZipRecruiter operates and makes decisions. You'll partner with RevOps, Decision Science, Product, and Engineering teams, working with technologies like Spark, Databricks, and Kubernetes to process billions of records daily. *We are open to leveling for this role based on experience and interview performance Key Focuses: Architect across business and engineering: Lead the design and implementation of data systems that serve both our operational business stakeholders (RevOps, Decision Science) and our product and engineering teams. Extend our internal AI platform: Contribute to and help shape the future with work that compounds across every analysis we run at Zip. Set the engineering bar for data: Bring software engineering rigor to data work: testing, CI/CD, code review, version control, observability and evangelize these practices across the team. Build and own data models: Translate complex, cross-domain business questions into robust, well-tested, reusable data sets and models. Partner with product engineering: Collaborate directly with engineering teams to embed analytical and data-modeling capabilities into product systems and pipelines. Mento

Job Description This is an opportunity for students and researchers of advanced data modeling and statistical learning methods to apply these techniques to market prediction and systematic trading. Job Responsibilities Pre-process (validate, clean, normalize, reduce dimension) very large data sets for model estimation and event studies Identify features and relationships useful for the predictive modeling of market dynamics Desirable Candidates Undergraduate, MS, or PhD candidates in finance, computer science, mathematics, physics, or other quantitative discipline Programming in any of the following: C++, Java, C#, MATLAB, R, Python, or Perl Strong analytical and quantitative skills Demonstrated interest in financial markets and systematic trading Clear, concise, and proactive communicator Detail-oriented Willing to take ownership of his/her work, working both independently and within a small team The annual base salary is $120,000-$180,000 (USD) which will be prorated based on internship start and end date. Actual compensation offered to the successful candidate may vary from posted hiring range based upon geographic location, work experience, education, and/or skill level, among other things.

Our vision is to transform how the world uses information to enrich life for all . Micron Technology is a world leader in innovating memory and storage solutions that accelerate the transformation of information into intelligence, inspiring the world to learn, communicate and advance faster than ever. Broad knowledge and experience in: Expertise in the field of Data Engineering, Business Intelligence, and Advanced Analytics. Supporting, and maintaining ETL/ELT processes using SSIS, Snowflake, and cloud-native data integration technologies. Proficient in writing advanced SQL queries in both SQLServer and Snowflake. Proficient in debugging ETL packages. Good knowledge of databases, data warehousing, dimensional data modeling, and data governance practices. Familiarity with cloud-based systems for data engineering, especially Google Cloud Platform (GCP) and BigQuery. Experience with workload automation, job scheduling, and monitoring tools such as Active Batch & RMJ. Supporting Business enterprise data pipelines and ensuring data availability, reliability, and performance. Experience in production support, handling incidents, identifying root causes, and resolving problems. Knowledge of building APIs and integrating data across multiple applications and platforms. Experience with Agile development methodologies and DevOps practices. Resolving transformation requirements and developing processes to bring structured and unstructured data from source systems into target data models. Working with Data Engineers, Data Scientists, and Business teams to support data quality, data preparation, and analytical workloads. <li