Data Engineering Manager

This is a fully remote position, open to applicants in New York.

📋 Description

• Oversee and enhance a team of data engineers tasked with managing both batch and streaming data systems.

• Lead technical execution across various layers including ingestion, transformation, modeling, and serving.

• Set engineering standards, implement code quality practices, and establish architectural review processes.

• Provide mentorship to engineers in the areas of distributed systems design, performance optimization, and production reliability.

• Ensure adherence to scalable data modeling standards and optimize query performance for analytical workloads.

• Advise on architectural decisions encompassing orchestration, schema evolution, partitioning strategies, and storage optimization.

• Collaborate with streaming engineers to synchronize batch and real-time data patterns into unified platform designs.

• Work closely with Data Product Management to align on roadmap priorities, SLAs, and platform KPIs.

• Partner with software engineers to integrate streaming systems, APIs, and microservices into the overall data ecosystem.

• Effectively communicate architectural trade-offs to stakeholders and address delivery risks and operational constraints.

• Conduct architectural reviews and shape the long-term strategy for the platform.

• Promote a culture centered on ownership, thorough documentation, and continuous improvement.

⛳️ Requirements

• Demonstrated experience in leading engineering teams that deliver large-scale production data platforms.

• Strong background in distributed systems engineering and cloud-native architectures.

• Extensive knowledge of data lakes, warehouses, and lakehouse architectures.

• Profound understanding of ETL/ELT frameworks, orchestration platforms, and distributed data processing systems.

• Solid grasp of Kafka-based architectures and event-driven data patterns.

• Proven track record in hiring, onboarding, and retaining high-performing engineers across different seniority levels.

• Dedication to fostering an inclusive, collaborative, and accountable team environment.

• Strong skills in sprint planning, capacity modeling, and roadmap sequencing.

• Ability to balance competing priorities among reliability, feature delivery, and technical debt reduction.

• Experience in establishing engineering KPIs such as reliability, latency, throughput, and deployment frequency.

• Excellent communication skills.

• Self-driven with a focus on quality.

🏝️ Benefits

• Medical

• Dental

• Vision

• 401(k) plan

• Life insurance coverage

• Disability benefits

• Tuition assistance program

• PTO

• Bonus eligible