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Lead Data Engineering Manager for Innovative Analytics and Infrastructure

LimeBike Germany GmbH

Remote · Canada Full-time Lead Yesterday

About the role

About

Elevate data engineering as a transformative Data Engineering Manager. Spearhead data infrastructure, ensure top-tier analytics, and support real-time insights in a remote role.
We seek an experienced Data Engineering Manager to oversee our engineering team, responsible for building and scaling critical data systems. This position combines leadership and technical acumen, emphasizing data architecture and the mastery of distributed systems. You will drive strategic initiatives that empower data scientists and analysts to gain insights reliably and efficiently.
Harness your data expertise to influence key analytics and infrastructure decisions while enhancing team capabilities and ensuring high-quality data access.

Key Responsibilities

  • Lead and mentor a high‑performing data engineering team
  • Define and prioritize technical strategy for data architecture
  • Ensure data quality and observability for mission‑critical pipelines
  • Implement best practices for data operations and governance
  • Collaborate with ML teams to streamline data for model readiness

Requirements

  • 7+ years of experience in data engineering roles
  • 2+ years in a leadership position within tech
  • Proficient with AWS, Snowflake, Spark, and SQL
  • Strong skills in data modeling and distributed processing
  • Excellent communication for cross‑functional impact

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Requirements

  • 7+ years of experience in data engineering roles
  • 2+ years in a leadership position within tech
  • Proficient with AWS, Snowflake, Spark, and SQL
  • Strong skills in data modeling and distributed processing
  • Excellent communication for cross-functional impact

Responsibilities

  • Lead and mentor a high-performing data engineering team
  • Define and prioritize technical strategy for data architecture
  • Ensure data quality and observability for mission-critical pipelines
  • Implement best practices for data operations and governance
  • Collaborate with ML teams to streamline data for model readiness

Skills

AWSData modelingDistributed processingMLSnowflakeSparkSQL

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