Data Engineering Manager-2

1. Data Engineering Delivery

• Lead end to end delivery of data pipelines and curated datasets supporting enterprise data products.

• Drive predictable execution aligned to sprint and release plans in partnership with Product and Delivery leadership.

• Establish and enforce engineering standards for pipeline design, data transformations, testing, and reusability.

• Proactively manage delivery risks, technical dependencies, and production issues.

2. Platform & Architecture Alignment

• Ensure engineering solutions align with enterprise data platform standards and lakehouse design patterns.

• Partner with platform and architecture teams to implement scalable, secure, and cost effective engineering solutions.

• Guide teams on appropriate use of shared platforms, environments, and datasets.

3. Data Quality, Governance & Trust

• Embed automated data quality checks and monitoring into pipelines as standard practice.

• Ensure metadata, lineage, and documentation requirements are met to support discoverability and governance.

• Partner with data governance and security teams to ensure compliance, auditability, and responsible data usage.

4. Engineering Excellence & Operational Readiness

• Drive CI/CD practices for data pipelines, including automated testing, deployments, and controlled promotions.

• Ensure pipelines are operationally ready with monitoring, alerting, and clear ownership for incident resolution.

• Continuously improve performance, reliability, and cost efficiency of data workloads.

5. Stakeholder & Cross Functional Collaboration

• Partner with Data Product Managers to translate product needs into executable engineering deliverables.

• Collaborate with Analytics and BI teams to ensure data assets support governed reporting and consumption.

• Communicate delivery status, risks, and trade offs clearly to stakeholders and leadership.

6. People Leadership & Team Development

• Manage, mentor, and develop a team of data engineers across experience levels.

• Set clear expectations around quality, delivery discipline, and operational ownership.

• Foster a culture of continuous improvement, documentation, and shared accountability.