Manager of Engineering leading a high - performing team in Drill Autonomy and Technology at Caterpillar. Overseeing engineering activities and collaborating with cross - functional teams.
About the role
- Data Engineering Manager leading data infrastructure for global fleet analytics at Lime. Overseeing data warehousing, governance, and supporting data operations and ML initiatives.
Responsibilities
- Lead, mentor, and scale a team of engineers focused on high-throughput data ingestion, processing, and storage solutions.
- Own the data roadmap by defining technical strategy, setting priorities for data architecture, and aligning with product and business stakeholders.
- Drive data reliability and observability strategy to ensure high data quality, lineage tracking, and uptime for mission-critical pipelines.
- Champion best practices in data ops, including version-controlled schemas (dbt), CI/CD for data pipelines, and automated testing.
- Drive innovation in ML-readiness by partnering with the ML Platform team to provide clean, feature-rich datasets for model training and inference.
- Foster a culture of data stewardship, ensuring data is discoverable, well-documented, and accessible across the organization.
- Partner with Security, Compliance, and Legal teams to implement robust data privacy and SOX-compliant access controls.
Requirements
- Bachelor’s or Master’s degree in Computer Science, Data Engineering, or a related technical field.
- 7+ years of experience in data engineering and distributed systems, with at least 2+ years in a technical leadership or management role.
- Proven success building and scaling modern data stacks on cloud providers (AWS preferred), including experience with Snowflake.
- Expertise in distributed processing (Spark, Flink, or Kafka) and workflow orchestration tools such as Airflow.
- Hands-on experience developing and debugging complex data transformations using Python and high-performance SQL.
- Strong understanding of data modeling and experience managing "Data as a Product" for internal consumers.
- Familiarity with data governance tools and practices (cataloging, lineage, and PII masking).
- Proven track record managing teams that deliver scalable, resilient data architectures in fast-growing environments.
- Excellent communication skills with the ability to translate complex data challenges into business impact for non-technical stakeholders.
Benefits
- Offers Equity
- Offers Bonus
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