Data Engineering Manager
What is this position about?
We're looking for a Data Engineering Manager to lead the design and delivery of complex data pipelines and integration solutions that power critical business workflows for our clients. You will own end-to-end data engineering initiatives from discovery and POC development through production deployment and optimization, while building and scaling a high-performing engineering team.
Your work will span platform-agnostic data architecture, high-volume record matching, deduplication, and near-real-time delivery systems. You will guide teams through complex data modeling decisions, performance optimization, and integration design, helping clients understand the tradeoffs between batch and real-time approaches, API-driven versus clean-room workflows, and infrastructure options.
What You Will Do
- Design and implement data ingestion architectures on Snowflake.
- Lead data engineering projects end to end—from discovery and requirements through POC validation to production deployment—while building and mentoring a high-performing engineering team
- Design platform-agnostic data pipelines and schemas that scale reliably at high volume, including complex data modeling for submit-grade-return workflows, identity graphs, record matching, and deduplication systems
- Own discovery pipeline initiatives and functional POCs, implementing high-volume matching logic and conducting comprehensive performance, load, and scale testing to validate architectural decisions
- Assess and optimize latency, throughput, connection stability, and integration options including APIs, batch delivery, and governed clean-room workflows
- Define data integration strategies and communicate tradeoffs clearly to clients, guiding infrastructure and tool selection based on performance requirements and business constraints
- Lead partner-facing API design and integration strategy, architecting batch versus real-time decisions and designing governed clean-room solutions for partner data exchange
- Establish technical standards for schema design, SQL quality, pipeline development, and production readiness across the team through reviews, mentoring, and knowledge sharing
What We Are Looking For
- 7+ years of hands-on data engineering experience, with proven expertise in building and deploying high-volume data pipelines in production
- 2+ years of direct team leadership or technical management experience
- Advanced SQL proficiency with deep expertise in schema and data-model design, complex joins, and performance optimization
- Proven track record with high-volume record matching, deduplication, and identity resolution systems
- Strong experience with platform-agnostic data engineering—ability to assess and implement solutions across Snowflake, Databricks, BigQuery, Redshift, and other platforms
- Demonstrated expertise in pipeline development, performance testing, latency and throughput analysis
- Experience designing and implementing batch and real-time data integration workflows
- Knowledge of governed clean-room solutions and data governance practices
- Solid understanding of API design, microservices patterns, and event-driven architectures
- A clear communicator equally comfortable with engineering teams and senior stakeholders
- Strong hiring and team-building instincts with proven mentoring experience
What about languages?
- English: Advanced (required for effective communication with global teams and client leadership).
How much experience must I have?
7+ years of hands-on data engineering experience in production environments, with 2+ years of direct team leadership or technical management responsibility.
Our Perks and Benefits:
📚 Learning Opportunities:
- Certifications in AWS (we are AWS Partners), Databricks, and Snowflake.
- Access to AI learning paths to stay up to date with the latest technologies.
- Study plans, courses, and additional certifications tailored to your role.
- Access to Udemy Bus