Engineering Data Analyst
The Engineering Data Analyst owns R&D analytics models, reporting reliability, data quality, and self-service insights. The role requires strong SQL, data modeling, stakeholder communication, and experience partnering with engineering teams.
About the job
Responsibilities
- Own data maintenance and reliability for key R&D internal Pigment applications and reporting, including FinOps, engineering metrics, and AI usage/impact.
- Maintain and evolve R&D analytics models, from curated datasets to scalable handoff with central Data when needed.
- Define best practices for structuring and scaling R&D applications and managing shared reference data.
- Implement automated quality checks and lightweight data contracts for trusted reporting.
- Create prompt templates and playbooks to enable self-service analytics.
- Prepare leadership decision boards and recurring reporting for staffing, reporting, and hiring discussions.
- Support small-scope initiatives, R&D All Hands, and R&D process automation such as onboarding access and timesheets.
- Review and improve the R&D Reporting model, including grain, definitions, consistency, and stakeholder usability.
- Collect insights about engineers’ work in connection with AI and prepare tested, curated boards for financial decision-making.
Requirements
- 3–7+ years, or equivalent experience, in Product Analytics, Data Analytics, or BI, ideally in a B2B SaaS environment.
- Strong SQL skills, including writing reliable, readable queries and building curated datasets.
- Experience with data modeling concepts such as facts and dimensions, grain, incremental builds, data contracts, and metric definitions.
- Ability to run analyses independently and communicate clearly with non-analytics audiences.
- Comfort working with ambiguous questions and iterating quickly.
- Experience partnering closely with engineering organizations, including DevEx, reliability, platform, or delivery metrics.
- Clear written communication covering problem statements, approaches, assumptions, limitations, and next steps.
- Stakeholder management skills for scoping, prioritization, and timeline expectations.
- A pragmatic approach to modeling: start simple, make it correct, then scale.
Nice-to-haves
- Familiarity with dbt or a similar transformation layer and modern analytics stacks.
- Experience with experimentation and basic causal inference.
- Understanding of observability concepts, including logs, metrics, traces, SLOs, and incident analysis.
- Exposure to cost analytics or FinOps.
Tools and Stack
- SQL and a data warehouse such as Snowflake or BigQuery
- dbt or a similar transformation layer
- BI tools such as Looker, Mode, Tableau, or Pigment
- Git for versioning models and documentation
Compensation and Benefits
- Competitive salary
- Equity
- Comprehensive health insurance with Alan Blue for employees and their families
- Trust and flexible working hours
- Remote-friendly policy
- Offices in Paris, London, New York, and Toronto
Skills
SQL, Data Modeling, dbt, Snowflake, BigQuery, Looker, Mode, Tableau, Pigment, Git, Finops, Causal Inference, Observability, SLOs, Data Contracts
Similar jobs
Data Analytics jobs
Virta Health
Remote
The Data Analyst supports Product Analytics and the Client Group by reconciling cross-system billing data, resolving discrepancies, and building durable data-quality controls and reporting. The role requires advanced Excel, strong SQL, and 5+ years of analytics, data, or finance-operations experience.
Thyme Care
Remote
Performs actuarial and financial analysis for value-based healthcare contracts, using claims data, SQL, forecasting models, and statistical methods to evaluate performance and support payer partnerships. Requires a quantitative bachelor's degree, ASA or near-ASA credentials, and at least two years of healthcare actuarial experience.
OpenLoop
Remote
Staff Data Analyst leads analytics strategy for telehealth platform, driving executive decisions on patient outcomes, compliance, and operations using advanced SQL, Python/R, and BI tools. Requires 8+ years experience, bachelor's degree, and healthcare domain knowledge.