Analytical Quality Assurance Director Jobs

About Us SharkNinja is a global product design and technology company, with a diversified portfolio of 5-star rated lifestyle solutions that positively impact people’s lives in homes around the world. Powered by two trusted, global brands, Shark and Ninja , the company has a proven track record of bringing disruptive innovation to market and developing one consumer product after another has allowed SharkNinja to enter multiple product categories, driving significant growth and market share gains. Headquartered in Needham, Massachusetts with more than 4,100 associates, the company’s products are sold at key retailers, online and offline, and through distributors around the world. AI at SharkNinja At SharkNinja, we’re building an AI-native culture. We’re not waiting for the future; we’re creating it. Our people are expected to experiment boldly, adopt new tools, and continuously raise what’s possible to create meaningful impact for our consumers. If you believe the best way to do your job hasn’t been invented yet, you’ll fit right in. *This role is hybrid 3x week onsite in Needham, MA The Senior Analyst, Global Purchasing, will serve as a key operational support resource for the Purchasing team and Procure-to-Pay platform. This role will act as a Procure-to-Pay administrator, responsible for day-to-day system support, ticket management, and business user assistance, while also contributing to projects related to SOX compliance, new module implementations, and country or regional rollouts. Additional support or project work for the broader global purchasing and procurement team may be required. The ideal candidate combines strong system knowledge with a service-oriented mindset and the ability to support both steady-state operations and project work. You are eager to bring experience and knowledge to improve a historical system, can direct your work and be a self-starter, jump into projects, and are an analytica

Elastic, the Search AI Company, enables everyone to find the answers they need in real time, using all their data, at scale — unleashing the potential of businesses and people. The Elastic Search AI Platform, used by more than 50% of the Fortune 500, brings together the precision of search and the intelligence of AI to enable everyone to accelerate the results that matter. By taking advantage of all structured and unstructured data — securing and protecting private information more effectively — Elastic’s complete, cloud-based solutions for search, security, and observability help organizations deliver on the promise of AI. What is The Role This is a hands-on build role that will develop and maintain HR's data pipelines on our GCP/BigQuery/dbt data model, with an AI-powered analytics layer on top. Core platform infrastructure is provisioned centrally; you'll help configure HR-specific pipelines and dbt modeling work on top of it, in partnership with our data scientist, and stand up recruiting reporting and insights as the first production use case on the new stack. This role reports directly to the Director of HR Analytics, with high visibility into architecture and stakeholder-facing decisions from day one. Your mission is to move the organization away from manual reporting and toward a mature, self-service environment where senior stakeholders get decision-ready answers, not just data. What You Will Be Doing Build and Deploy Scalable Analytics Build and maintain data pipelines in BigQuery/dbt, on infrastructure provisioned by the central data platform team, that link HR data across the employee lifecycle (Workday, Greenhouse, Qualtrics, ServiceNow), so we can trace how hiring decisions affect long-term engagement and retention. Support and enhance the AI-powered analytics user experience. Develop scalable, self-service dashboards that reduce time spent on reactive, one-off data requests. Implement data governance practices (access controls, validation, documentati

About Us At LangChain, our mission is to make intelligent agents ubiquitous. We build the foundation for agent engineering in the real world, helping developers move from prototypes to production-ready AI agents that teams can rely on. We began as widely adopted open-source tools and have grown to also offer a platform for building, evaluating, deploying, and operating agents at scale. With $125M raised at Series B from IVP, Sequoia, Benchmark, CapitalG, and Sapphire Ventures, we’re at a stage where we’re continuing to develop new products, growth is accelerating, and all team members have meaningful impact on what we build and how we work together. LangChain is a place where your contributions can shape how this technology shows up in the real world. Today, our platform includes LangSmith (Observability, Evaluation, Deployment, Fleet, and Sandboxes), our open source frameworks (LangChain, LangGraph, and Deep Agents), and the newly launched LangSmith Engine for autonomous agent improvement. We have 100M+ monthly open source downloads, 6,000+ active LangSmith customers, and 5 of the Fortune 10 use LangSmith in production (+ 35% of the Fortune 500 overall), including teams at Klarna, Clay, Coinbase, Workday, Lyft, Cloudflare, Harvey, Rippling, Vanta, LinkedIn, Monday.com, Nvidia, and Bridgewater. About the team: We are a small but mighty team of three analytics engineers powering LangChain’s internal data infrastructure and analytics. We’re a full-stack team, meaning we work end-to-end across the data stack, from data ingestion to enabling self-serve agentic analytics. Learn more about what we’ve built so far here ! About the role: We are expanding our data team and looking for a analytics engineer to join us. We build products used by elite companies and over a million developers, and data plays a critical role in sharping our strategies and decision making. In this role you will help lay the foundation for business teams to diagnose issues, uncover opportunities, an

At Affirm, we exist for the moments that matter—giving people a clear, predictable way to pay over time, with no hidden fees, no surprises, and no tradeoffs on what matters most. Financial Systems owns the data and reporting foundation for Accounting, and the operational reliability of the pipelines that power reporting, reconciliations, and automation. We are building a single source of truth for financial information using dbt and Snowflake to enable scalable BI and process automation across the org. We are hiring an Analytics Engineer focused on maintaining and optimizing our finance data platform , improving reliability, efficiency, and performance of our pipelines and core datasets. This role is ideal for someone who enjoys operational ownership, building strong foundations, and making data systems easier and safer to run at scale. What You’ll Do Build and maintain dbt models and core datasets that support Accounting reporting and downstream automation use cases. Improve platform reliability through strong testing patterns, alerting, and runbooks. Own and document data pipelines and lineage, ensuring changes are understandable and auditable. Identify, troubleshoot, and resolve production data issues, and drive root-cause fixes. Optimize performance and cost in Snowflake and dbt to support scaling needs. Partner with engineering and business stakeholders to translate requirements into durable, well-tested data assets. Contribute to the team’s best practices in version control, code review, documentation, and release hygiene (GitHub-based workflows). What We Look For 3+ years of experience in analytics engineering, data engineering, or similar roles working with production data systems. Strong SQL skills and hands-on experience building in dbt (modeling, testing, documentation). Experience operating in a modern development workflow: Git and pull-request based collaboration (GitHub preferred). Familiarity with standard IDEs and collaborative debugging practices. E

About Taskrabbit: Taskrabbit is a marketplace platform that conveniently connects people with Taskers to handle everyday home to-do’s, such as furniture assembly, handyman work, moving help, and much more. At Taskrabbit, we want to transform lives one task at a time. As a company we celebrate innovation, inclusion and hard work. Our culture is collaborative, pragmatic, and fast-paced. We’re looking for talented, entrepreneurially minded and data-driven people who also have a passion for helping people do what they love. Together with IKEA, we’re creating more opportunities for people to earn a consistent, meaningful income on their own terms by building lasting relationships with clients in communities around the world. Taskrabbit is a hybrid company with employees distributed across the US and EU and a Built In — Best Places to Work (2022, 2023, 2024, 2025) continually ranked across multiple national and regional categories. Join us at Taskrabbit, where your work will be meaningful, your ideas valued, and your potential unleashed! Prior to applying please note: We are currently unable to provide visa sponsorship for this position (including H-1B, OPT, F1, CPT or other employment-based visas). Candidates must be legally authorized to work in the United States without employer sponsorship now or in the future. This role is hybrid, requiring 2 days in office at our San Francisco hub every Tuesday & Wednesday (located at 130 Sutter St, San Francisco, CA). About the Role Taskrabbit's Data Engineering team is looking for a Senior Analytics Engineer to build and maintain the data models that power decision-making across the company. You'll sit at the intersection of data engineering and analytics — turning raw data into trusted, well-documented datasets that business teams rely on every day. This is a hands-on, individual-contributor role: you'll own key parts of the data model layer end to end, partnering closely with data engineers, analysts, and business stake

Job Overview We are looking for an Analytics Engineer who will own dbt Cloud in our organisation and maintain the analytics pipelines built on top of it. You will administer dbt Cloud across multiple independent projects, keep our business-critical pipelines running (including finance data models), and support analysts in other teams as a mentor and go-to person for dbt. Our stack is Snowflake, dbt and AWS, with Python for tooling and automation. We are also building AI-assisted and agentic workflows into our daily work, and you will take an active part in this. Reports to Director of Mobile and New Games What will you do? Administer dbt Cloud for the whole organisation: project setup, environments, permissions, CI/CD, version upgrades and cost control Set up and support multiple independent dbt projects, define common standards and conventions so teams stay aligned Develop and maintain production dbt pipelines, including complex finance models where accuracy and trust are critical Mentor analysts on dbt, SQL modeling, testing and code review Tune Snowflake performance and cost, improve pipeline reliability and monitoring Build tooling and automation in Python (AWS Lambda, S3, orchestration, metadata workflows) Drive AI adoption in our analytics engineering work: build common AI skills for dbt development (documentation, testing, code generation) and automated agentic workflows that the whole team can reuse Follow current trends in AI tooling and agentic systems, evaluate new approaches and bring the useful ones into the team What are we looking for? 4+ years of experience in analytics engineering, data engineering or a similar role Strong hands-on dbt experience, ideally including dbt Cloud administration (projects, environments, jobs, CI/CD), not only model development Strong SQL and data modeling skills Production experience with Snowflake, including performance tuning and cost awareness Python for data tooling and automation Experience with AWS services used in

Job Overview We are looking for an Analytics Engineer who will own dbt Cloud in our organisation and maintain the analytics pipelines built on top of it. You will administer dbt Cloud across multiple independent projects, keep our business-critical pipelines running (including finance data models), and support analysts in other teams as a mentor and go-to person for dbt. Our stack is Snowflake, dbt and AWS, with Python for tooling and automation. We are also building AI-assisted and agentic workflows into our daily work, and you will take an active part in this. Reports to Director of Mobile and New Games What will you do? Administer dbt Cloud for the whole organisation: project setup, environments, permissions, CI/CD, version upgrades and cost control Set up and support multiple independent dbt projects, define common standards and conventions so teams stay aligned Develop and maintain production dbt pipelines, including complex finance models where accuracy and trust are critical Mentor analysts on dbt, SQL modeling, testing and code review Tune Snowflake performance and cost, improve pipeline reliability and monitoring Build tooling and automation in Python (AWS Lambda, S3, orchestration, metadata workflows) Drive AI adoption in our analytics engineering work: build common AI skills for dbt development (documentation, testing, code generation) and automated agentic workflows that the whole team can reuse Follow current trends in AI tooling and agentic systems, evaluate new approaches and bring the useful ones into the team What are we looking for? 4+ years of experience in analytics engineering, data engineering or a similar role Strong hands-on dbt experience, ideally including dbt Cloud administration (projects, environments, jobs, CI/CD), not only model development Strong SQL and data modeling skills Production experience with Snowflake, including performance tuning and cost awareness Python for data tooling and automation Experience with AWS services used in

Job Overview We are looking for an Analytics Engineer who will own dbt Cloud in our organisation and maintain the analytics pipelines built on top of it. You will administer dbt Cloud across multiple independent projects, keep our business-critical pipelines running (including finance data models), and support analysts in other teams as a mentor and go-to person for dbt. Our stack is Snowflake, dbt and AWS, with Python for tooling and automation. We are also building AI-assisted and agentic workflows into our daily work, and you will take an active part in this. Reports to Director of Mobile and New Games What will you do? Administer dbt Cloud for the whole organisation: project setup, environments, permissions, CI/CD, version upgrades and cost control Set up and support multiple independent dbt projects, define common standards and conventions so teams stay aligned Develop and maintain production dbt pipelines, including complex finance models where accuracy and trust are critical Mentor analysts on dbt, SQL modeling, testing and code review Tune Snowflake performance and cost, improve pipeline reliability and monitoring Build tooling and automation in Python (AWS Lambda, S3, orchestration, metadata workflows) Drive AI adoption in our analytics engineering work: build common AI skills for dbt development (documentation, testing, code generation) and automated agentic workflows that the whole team can reuse Follow current trends in AI tooling and agentic systems, evaluate new approaches and bring the useful ones into the team What are we looking for? 4+ years of experience in analytics engineering, data engineering or a similar role Strong hands-on dbt experience, ideally including dbt Cloud administration (projects, environments, jobs, CI/CD), not only model development Strong SQL and data modeling skills Production experience with Snowflake, including performance tuning and cost awareness Python for data tooling and automation Experience with AWS services used in

Job Overview We are looking for an Analytics Engineer who will own dbt Cloud in our organisation and maintain the analytics pipelines built on top of it. You will administer dbt Cloud across multiple independent projects, keep our business-critical pipelines running (including finance data models), and support analysts in other teams as a mentor and go-to person for dbt. Our stack is Snowflake, dbt and AWS, with Python for tooling and automation. We are also building AI-assisted and agentic workflows into our daily work, and you will take an active part in this. Reports to Director of Mobile and New Games What will you do? Administer dbt Cloud for the whole organisation: project setup, environments, permissions, CI/CD, version upgrades and cost control Set up and support multiple independent dbt projects, define common standards and conventions so teams stay aligned Develop and maintain production dbt pipelines, including complex finance models where accuracy and trust are critical Mentor analysts on dbt, SQL modeling, testing and code review Tune Snowflake performance and cost, improve pipeline reliability and monitoring Build tooling and automation in Python (AWS Lambda, S3, orchestration, metadata workflows) Drive AI adoption in our analytics engineering work: build common AI skills for dbt development (documentation, testing, code generation) and automated agentic workflows that the whole team can reuse Follow current trends in AI tooling and agentic systems, evaluate new approaches and bring the useful ones into the team What are we looking for? 4+ years of experience in analytics engineering, data engineering or a similar role Strong hands-on dbt experience, ideally including dbt Cloud administration (projects, environments, jobs, CI/CD), not only model development Strong SQL and data modeling skills Production experience with Snowflake, including performance tuning and cost awareness Python for data tooling and automation Experience with AWS services used in

About Us: AI needs a new infrastructure layer. We're building it at Modal. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Ramp , Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We've passed $1B in annualized run rate, up 15x from a year ago. In October 2026 we raised a $750M Series D led by Accel at a $15.75B valuation. Our team includes creators of popular open-source projects (e.g., Seaborn , Luigi ), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. About the Data Team: We’re growing our Data team and are looking for our first few key hires to build self-serve data tools and drive business strategy in the right direction. The mission of the Modal Data team is to make it easy to track company goals, make evidence-backed decisions, and prioritize the right work. We do this via: Self-serve AI analytics tools (Hex, Snowflake) Embedding with teams as a “data adviser”, providing strategic analysis and consulting What You'll Do: Contribute to building the most modern analytics stack in Data today to support AI-driven self-serve analysis, key metrics tracking, and external customer reporting Influence work on new products like LLM Inference Endpoints through product analytics tracking Identify millions of dollars of cost savings and optimization across our tools and financial operations Write data pipelines that power the operations of our business, such as ou

Shape the Future with Dun & Bradstreet At Dun & Bradstreet, we believe data has the power to create a better tomorrow. As a global leader in business decisioning data and analytics, we help companies worldwide grow, manage risk, and innovate. Since 1841, businesses have trusted us to turn uncertainty into opportunity. We’re a diverse, global team that values creativity, collaboration, and bold ideas. Are you ready to make an impact and help shape what’s next? Join us! Explore opportunities at dnb.com/careers. The Analytics Advisor III is a vital role in the sales process working in conjunction with the sales team to drive Analytic and AI revenue within existing customers and new logo prospects. The Analytics Advisor III is focused primarily on the Discovery through Proof stages of the sales cycle, the Analytics Advisor will help build the “value story” to maximize customer success. The Analytics Advisor III is responsible for gaining a deep understanding of the customers’ business challenges, determining where Dun & Bradstreet’s analytic solutions can provide value, proposing the best solution(s) to meet customer needs and creating a compelling business case to close on the Analytics and AI sales opportunity. This role will be managing a book of $10M+ in Analytics/AI sales across Global/Tier 1 accounts. Essential Key Responsibilities: Drive meaningful customer value and sustained YOY sales growth selling Dun & Bradstreet’s Analytic and AI solutions to customers and prospects. Drive new Analytic and AI business through demand creation, opportunity qualification, solution identification and value enablement. Actively identify, prospect and develop new business opportunities within a relatively small number of existing and new accounts (heavy up-sell / cross-sell responsibilities). Conduct business based conversations to identify stakeholders, business process, KPI”s and critical success factors around an opportunit

Our Global Structure Deliveroo is now part of DoorDash, bringing together teams with even greater reach, scale, and ambition. Depending on your role, you may collaborate with teammates, systems, and leaders across DoorDash and Wolt. Together, we’re unlocking new possibilities as one global team. Join us in our mission to transform the way people shop and eat, where impact, innovation and growth drive everything we do. Our Analytics organisation sits at the heart of Deliveroo powering decision-making across our 3 sided marketplace. We’re looking for an Analytics Engineering Manager to join our London team. This is a hybrid role, with 3 days per week on-site. In this role, you’ll lead a team of Analytics Engineers embedded in a key business domain, owning the pipelines, models and metrics that power day-to-day decisions and building the data foundations your stakeholders rely on. About the Analytics Engineering Org Analytics Engineering is a core pillar of Deliveroo’s Analytics organisation, alongside Data Science. With over 70 Analytics Engineers across the UK and India, we are embedded directly within product and business domains, owning the pipelines, models and metrics that power decision-making at scale: from self-serve AI-enabled analytics and experimentation through to executive reporting and strategic planning. The discipline is evolving fast. With new tooling changing how we work, we are shifting from building data pipelines to building AI first data products, developing rich semantic and data context layers and empowering self-serve data users. This role leads that work across a defined business domain, directly managing a team of Analytics Engineers and helping shape AE standards, culture and direction across the wider org. What You'll Be Doing Directly lead a team of Analytics Engineers embedded in a defined business domain, owning their performance, development and wellbeing Own the AE roadmap for your domain, identifying the highest-

MyPrize is the fastest growing free-to-play social gaming and social markets platform in the world, redefining how people play, watch, and connect with one another and with gaming and markets online. Pioneering multiplayer experiences where users can join forces with creators, streamers, and friends, MyPrize provides a platform built for shared moments and massive communities. MyPrize transcends boundaries, giving players and fans what they have been desperately craving: an all-in-one platform that combines the best of online gaming, live streaming, and social markets, powered by MyPrize's proprietary AI personalization engine. With SOC 2 Type 1 certification, MyPrize maintains institutional-grade security while building the future of online entertainment. We're seeking a Marketing Analytics Manager to join our growing Analytics team full time. This is an exciting opportunity to be the first embedded analytics hire at MyPrize, building the foundational attribution and reporting infrastructure that connects marketing investment to player value. The Role: As Marketing Analytics Manager at MyPrize, you'll own measurement of acquisition efficiency and marketing ROI across paid, organic, and lifecycle channels, connecting media spend to player value so marketing investment decisions are evidence-based. You'll be the first embedded analytics hire, working directly with the Head of Analytics to stand up the function's foundational attribution and reporting infrastructure. What you will do at MyPrize: Paid Social Analytics & Optimization: Monitor and optimize paid social campaigns across Meta Ads Manager and TikTok Ads Manager — audience segmentation, budget allocation, and A/B testing — and flag data-feed or tracking issues that affect measurement accuracy. Paid Search Agency Collaboration: Serve as the analytics point of contact for paid search agencies, translating performance and player-value trends into budget, bid-strategy, and keyword recommendations, and

Our mission and customers: We are creating the freedom for SMEs to succeed by delivering Europe's leading finance workspace with banking at its core, augmented by financial tools. We are proud to be rated 4.8 on Trustpilot, based on 55,000+ reviews. Our culture puts customer satisfaction at the core of what we do, as proven by our Net Promoter Score of 75 (more about our culture here). Our journey: Founded in 2017 by Alexandre and Steve, Qonto has grown to 1,600+ Qontoers serving over 600,000+ customers across 8 European countries. We have been profitable since 2023, and we are just getting started. Our beliefs: We hire for skills and potential. With 80+ nationalities, 45% women, of which 56% of women in our leadership team, diversity isn't a program; It's who we are. We've built a discrimination-free hiring process because the best teams are built on merit. AI at Qonto: AI is deeply embedded in how we work (here) - Every Qontoer gets unlimited access to the best AI tools. We want people who experiment without waiting for permission, push AI beyond the obvious, know when to trust it, and when to question it. ------------------------------------------------------------------------------------------------------ ➡️ Mission: Join us as Analytics Engineer x Business Analytics and become the person our Business Analytics teams can build on without a second thought. You will own end-to-end the data models feeding Product, Growth, and Ops Finance analytics — designing scalable dbt models, pushing back on requests that would trade reliability for speed, and helping the team migrate to Omni and a real semantic layer. You will work closely with Jules Jeanroy, our Analytics Engineering Manager, and partner daily with Business Analysts across Product, Growth, and Ops Finance. The team is at a pivotal moment — investing in scalability, cutting technical debt, and building the standards that will define how Analytics Engineering works at Qonto for years to come. ➡️ As an Analyti

Analytics Manager, Commercialization Atari, Inc. Remote About Us Atari has been a bright spot in the struggling games industry: quietly but quickly growing year-over-year. The Commercial team has played a critical part in making that possible. We are looking for someone to lead analysis on a large, complex, quickly growing dataset and help us make better commercial decisions every day. This is a deliberately unusual analytics job. Over the past year we’ve built an internal AI system called the “Commercial Brain” that scopes, runs, and self-checks commercial analyses. It is very powerful but also often makes mistakes in ways that are easy to miss and expensive to ship. Operating the Commercial Brain, catching its mistakes, and improving it is the central function of this role. This is a high-autonomy role for someone who is energized by ambiguous problems, rigorous by instinct, and excited about using AI to do more with less. Atari, and especially the Commercial team, runs much closer to a startup than to a big company. You’ll get real ownership, fast decisions, and thin process; if you need mature structure around you to do your best work, this role will frustrate you. In this role, you’ll spend most of your time deep in analysis; not building data pipelines, dashboards, or production systems. Your output is judgment, insight, and commercial recommendations that directly shape revenue. You’ll sit at the intersection of AI, data analysis, commercial strategy, and financial modeling. You’ll work closely with our Business Operations Manager and report directly to our Director of Commercial. What you’ll do Operate the Commercial Brain Scope analyses with the Commercial Brain, interrogate its reasoning, and find its errors and unstated assumptions before they reach a decision. Act as the second reviewer of record on analyses that today have only one. Verification is a primary deliverable of this role. Own the empirical loop: every significant decision record