Director, Analytics Engineering
$270,000–$330,000 year
On-siteNew York, United States or Manhattan, New York, United States
Job Summary
Define and drive the Analytics Engineering and BI strategy, owning the roadmap and P&L for data warehousing and business intelligence across the organization. Act as a hands-on engineer optimizing complex SQL, reviewing dbt models, and troubleshooting high-priority pipeline issues in BigQuery. Lead the design of robust dimensional models and aggregation layers, collaborating with stakeholders to translate requirements into high-fidelity data models for Looker. Manage and grow the Analytics Engineering team, including an offshore group, by defining career ladders, conducting performance reviews, and fostering technical excellence. Establish frameworks for data reconciliation, quality management, and security to ensure absolute confidence in data integrity. Collaborate with Data Platform Engineers to implement modern tooling for ingestion, transformation, and observability while establishing robust governance practices.
Required Qualifications
- 10+ years of experience in Analytics Engineering, Data Engineering, or Data Architecture
- at least 5+ years in a leadership or management capacity
- Proven track record of building and scaling enterprise-grade Data Warehouses from the ground up
- Deep mastery of Kimball/Star Schema methodologies
- Expert-level SQL and performance tuning skills
- Significant experience with dbt
- Significant experience with BigQuery or similar MPP like Snowflake
- Significant experience with orchestration tools like Airflow
- Intermediate to advanced level programming skills in Python or other languages
- Extensive experience building scalable data models and reporting layers in Looker (LookML) or similar enterprise BI tools
- Strong experience with cloud ecosystems like GCP or AWS
- Ability to explain complex technical concepts to non-technical stakeholders
Desired Qualifications
- Direct experience in the Fintech or D2C domains
- Experience managing distributed or hybrid teams
- Familiarity with data mesh or data contract methodologies
- Experience working with and managing a team in different time-zones
- experience with dbt (preferred)
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