Data Engineering Manager

You will lead a team of data engineers building high-quality, scalable data products and infrastructure. You will balance people management with technical delivery, mentoring engineers, guiding solution design, and collaborating across teams. You will guide the design and implementation of data pipelines, platforms, and data products, review architecture and code, and jump in hands-on to resolve complex engineering challenges. You will partner with product managers, data scientists, analysts, and business stakeholders to translate business needs into engineering plans. You will promote operational stability through monitoring, alerting, and incident response, advocate for high standards in data quality and governance, and drive continuous improvement in workflows and team productivity.

Responsibilities

• Lead a team of data engineers through coaching, mentorship, and technical guidance
• Support individual career development and performance feedback, creating growth opportunities for the team
• Foster a collaborative, inclusive, and high-performance team culture
• Guide the design and implementation of scalable data pipelines, platforms, and data products
• Review architecture and code, provide technical direction, and help resolve complex engineering challenges hands-on when needed
• Ensure delivery of high-quality, reliable solutions aligned with business goals and engineering best practices
• Partner with product managers, data scientists, analysts, and business stakeholders to understand requirements and prioritize work
• Translate business needs into actionable engineering plans and ensure timely delivery of key projects
• Communicate clearly across technical and non-technical teams to align on priorities and progress
• Promote operational stability and reliability of data pipelines and systems through monitoring, alerting, and incident response
• Advocate for high standards in data quality, governance, and compliance
• Drive continuous improvement in development workflows and team productivity

Requirements

• 6+ years of experience in data engineering or software engineering, with at least 1-2 years in a team leadership or mentorship role
• Strong technical background in building and maintaining data pipelines and platforms using tools like Spark, dbt, Airflow, Kafka, or Databricks
• Proficiency in SQL and one or more programming languages (e.g., Python, Scala, or Java)
• Experience with cloud data platforms (e.g., AWS, GCP, or Azure)
• Strong communication and collaboration skills with a passion for working across teams
• Prior experience in a people management or tech lead role within a data engineering or analytics team (preferred)
• Familiarity with machine learning workflows, data observability, and streaming architectures (preferred)
• Experience working in a product-driven, customer-focused organization (preferred)
• Understanding of data privacy, security, and compliance frameworks (preferred)

Benefits

• Health plans including fertility and family planning programs, mental health support, and fitness benefits
• Generous paid time off (PTO and sick leave)
• Annual bonus and long-term incentive opportunities
• 401k with up to a 5% match
• Commuter benefits
• Pet insurance
• Medical, vision, and dental insurance
• Life insurance
• Disability insurance
• Stock program participation
• 14 paid company holidays