Data Engineering Manager

About the Role

Key Responsibilities

• Lead a team of data engineers through coaching, mentorship, and technical guidance.
• Support individual career development and performance feedback, creating growth opportunities for your 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 by being 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 detailed 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 by collaborating with platform and data governance teams.
• 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.

Nice to Have

• Prior experience in a people management or tech lead role within a data engineering or analytics team.
• Understanding of Risk or Trading terminology.
• Familiarity with machine learning workflows, data observability, and streaming architectures.
• Experience working in a product-driven, customer-focused organization.
• Understanding of data privacy, security, and compliance frameworks.

Qualifications

• Educational background is not explicitly specified, but at least 6+ years of relevant experience is required.

Benefits & Perks

• Health plans including programs for fertility and family planning, mental health support, and fitness benefits.
• Generous paid time off (PTO & sick leave).
• Annual bonus and long-term incentive opportunities based on performance.
• 401k with up to a 5% match.
• Commuter benefits, pet insurance, and more.
• Paid personal time off and 14 paid company holidays.
• Paid sick time in accordance with applicable laws.