1. Data Pipeline Development & Design

Design and build complex data pipelines for ingestion, transformation, and delivery on modern data platforms.

Lead the design of reusable transformation logic and scalable data models that follow established engineering standards.

Make technical design decisions for curated datasets, balancing performance, reliability, and reusability.

Review code and designs from other engineers to maintain quality and consistency.

2. Data Quality & Governance Support

Implement and improve automated data validation and quality checks as part of pipeline development.

Lead investigation and resolution of complex data quality issues.

Ensure metadata, documentation, and lineage are maintained to support discoverability and governance.

3. Operational Readiness & Reliability

Drive CI/CD practices for data deployments, including testing and environment promotion.

Lead troubleshooting and root-cause analysis for complex pipeline failures.

Contribute to operational practices for incident handling and continuous improvement.

4. Technical Mentorship & Collaboration

Mentor junior and mid-level data engineers on coding standards, design patterns, and troubleshooting.

Work with Product Managers and stakeholders to clarify requirements and data expectations.

Partner with analytics and BI teams to ensure data assets support reporting and insights.

Communicate clearly on progress, risks, and dependencies, including in technical design discussions.