- Architect and develop high quality data assets for product and analytics use cases, as well as for sharing with external partners
- Collaborate and build relationships with partners including backend/client, data science, analytics, and ML
- Develop frameworks, tools, and dashboards to scale insight generation to meet critical business, product, and regulatory requirements
- Translate ambiguously expressed data requirements into efficient, scalable, and impactful deliverables.
- Present product and technical deep dives to key stakeholders
- Influence the trajectory of data in decision making
- Improve trust in our data by championing for data quality across the stack
- 9+ years of experience experience in Analytics Engineering, Data Science, Data Engineering, or similar field
- Expertise in SQL and proficiency in at least one data engineering language, such as Python or Scala
- An ability to navigate metric and data considerations in the Trust domain, including uncertain risk assessment and late-landing signals.
- Expertise creating metrics, evaluating effectiveness of defenses - ex: rules and ML models utilizing evaluation and experiment data.
- Experience with Tableau and data visualization tools generally
- Experience with an ETL framework like Airflow
- Excellent communication skills with a history of strong collaborations with technical and non-technical partners
- Expertise with data warehousing and modeling. Hands-on experience with relational databases (e.g., PostgreSQL, MySQL) and columnar databases (e.g., Redshift, BigQuery, HBase, ClickHouse)
- Strong problem-solving skills and the ability to troubleshoot complex data issues
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