Data Engineering Manager

Key Responsibilities

• Lead & Scale Data Engineering Teams
• Manage and develop a team of data engineers responsible for batch and streaming data systems.
• Drive technical execution across ingestion, transformation, modeling, and serving layers.
• Establish engineering standards, code quality practices, and architectural review processes.
• Mentor engineers in distributed systems design, performance optimization, and production reliability.
• Architect Scalable Data Platforms
• Ensure scalable data modeling standards and efficient query performance across analytical workloads.
• Guide decisions about architecture, including orchestration and schema evolution, and storage optimization.
• Partner with streaming engineers to align batch and real-time data patterns into cohesive platform designs.
• Cross-Functional Collaboration
• Partner closely with Data Product Management to align roadmap priorities, SLAs, and platform KPIs.
• Collaborate with software engineers to integrate streaming systems, APIs, and microservices into the broader data ecosystem.
• Clearly communicate architectural tradeoffs to stakeholders.
• Share delivery risks and operational constraints as well.

Technical Leadership

• Lead architectural reviews and drive long-term platform strategy.
• Foster a culture of ownership, documentation, and continuous improvement.

Required Skills & Experience

• Modern Data Architecture
• Strong expertise in data lakes, warehouses, and lakehouse architectures.
• Solid understanding of ETL/ELT frameworks, orchestration platforms, and distributed data processing systems.
• Deep understanding of Kafka-based architectures and event-driven data patterns.
• Team Development & Coaching
• Proven experience hiring, onboarding, and retaining high-performing engineers across varying seniority levels.
• Commitment to building an inclusive, collaborative, and accountable team culture.
• Execution & Delivery Leadership
• Strong sprint planning, capacity modeling, and roadmap sequencing skills.
• Ability to manage competing priorities across reliability, feature delivery, and technical debt reduction.
• Experience establishing engineering KPIs such as reliability, latency, throughput, and deployment frequency.
• Required Qualifications
• Proven experience leading engineering teams delivering large-scale production data platforms.
• Strong foundation in distributed systems engineering and cloud-native architecture.
• Great communication skills.
• Collaboration with different teams.
• Self-motivated.
• Focus on quality.
• A commitment to engineering excellence and operational discipline is essential.