Manager, Data Engineering

About the Role

Key Responsibilities

• Be the go-to expert for data engineering best practices, architecture, and latest technologies.
• Provide strategic guidance on data platform modernization, scalability, and governance.
• Stay ahead of industry trends, ensuring the team adopts modern solutions.
• Lead technical training sessions, upskilling engineers on advanced data engineering concepts.
• Foster a culture of learning, encouraging innovation and experimentation.
• Be the trusted advisor to interdepartmental teams, ensuring clear agreement between business and technical goals.
• Represent the data engineering function in executive discussions, advocating for scalable solutions.
• Collaborate with product, analytics, and engineering teams to promote data-driven decision-making.
• Establish data governance policies, ensuring compliance and security.
• Design and increase scalable data pipelines, ensuring efficiency and reliability.
• Troubleshoot complex data challenges, providing expert-level solutions.
• Guide the team in evaluating new tools and technologies, balancing innovation with stability.

Requirements

• 8+ years of hands-on experience in data engineering and software development.
• 3+ years of people management experience.
• Solid knowledge of data architecture, pipelines, and governance.
• Experience optimizing data systems.
• Experience with BI tools (i.e., Tableau or Superset).
• Experience managing large-scale data sets, handling Terabytes of data and billions of records (across structured and unstructured datasets).
• Experience implementing compute and orchestration tools like Databricks and Airflow.
• Experience with AWS services (i.e., EMR Spark, Redshift, and S3) or GCP services (i.e., BigQuery, Google Storage, Looker, or Google Analytics).
• Experience in event data collection tools such as Snowplow, Segment, Google Tag Manager, Tealium, or mParticle.
• Experience translating complex technical concepts into actionable insights.
• Willingness to explore the latest technologies.

Nice to Have

• Experience with cloud ecosystems (AWS and GCP).
• Experience with data orchestration and compute tools.
• Familiarity with event data collection tools.

Qualifications

• Educational background is not explicitly specified, but extensive experience in data engineering and management is required.

Benefits & Perks

• Salary plus performance bonus earning potential, paid annually.
• Flexible time off policies.
• Generous medical, dental, vision, STD, LTD, and life insurance.
• Health Saving Account (HSA) program.
• Health care and dependent care FSA.
• 401(k) plan with employer match.
• Employer paid commuter benefit.
• Support program for new parents.
• Pet insurance and pet-friendly offices.