Data Engineering Team Lead

At this company, reliable and scalable data infrastructure isn’t just a technical goal - it’s central to its ability to power AI-driven innovation and enrich the product offerings. As Data Engineering Team Lead, you’ll combine hands-on technical expertise with people-first leadership. You’ll own the strategy, architecture, and delivery of its production data layer and guide a growing team of data engineers to build the foundations that enable data-powered product development across the company.

What You’ll Do

• Set Vision & Roadmap: Define the data engineering strategy in partnership with product, AI, and platform leads.


• Stay Hands-On: Lead critical design reviews and own complex components (~80% coding), troubleshooting as needed.


• Lead & Grow Team: Manage, hire, and mentor a high-performing team, driving career growth and accountability.


• Own the Data Platform: Build and scale real-time and batch infrastructure with strong SLAs and compliance.


• Ensure Quality: Establish standards for modeling, observability, orchestration, and governance.


• Collaborate Cross-Functionally: Partner with backend, platform, AI/ML, and product teams to deliver data-powered features.


• Champion Excellence: Promote data best practices and foster a culture of ownership and improvement.

• 7+ years of professional experience in data engineering, with 2+ years leading or managing engineers.


• Proven track record of building and operating production-grade data platforms (streaming and batch) using technologies such as Kafka, ClickHouse, Flink, Airflow, dbt, Snowflake, PostgreSQL,or equivalents.


• Advanced proficiency in SQL and Python.


• Demonstrated ability to set technical direction, prioritize roadmaps, and deliver results through others.


• Strong understanding of data architecture, reliability, scalability, and best practices for AI/ML pipelines.


• Excellent communication and collaboration skills; comfortable influencing senior stakeholders and working cross-functionally.


• Bachelor’s or Master’s degree in Computer Science, Information Systems, or equivalent experience.

Bonus Points

• Experience transitioning from monolithic data platforms to Data Mesh or decentralized data ownership models.


• Background in implementing data governance frameworks or compliance (e.g., GDPR, CCPA).


• Prior success leading teams that built platforms supporting AI/ML workloads end-to-end.


• Familiarity with infrastructure-as-code (e.g., Terraform) and cloud-native data services (AWS, GCP, or Azure).