Data Engineer III

The Data Engineer III plays a critical role in modernizing and scaling the Program’s data ecosystem by designing, building, and optimizing cloud-native data solutions on a modern technology stack.

The role is responsible for leading the design and implementation of program’s data pipelines, data models, and integration frameworks leveraging PostgreSQL, Python, SQL, AWS Grafana, AWS Quicksight, Apache AirFlow, and modern DevOps practices. The data engineer role brings significant experience delivering enterprise-scale data platforms, implementing cloud data architectures, and collaborating with technical stakeholders in fast-paced Agile environments.

Key Responsibilities:

• Partner with business stakeholders, product owners, architects, and technical teams to understand business objectives, data requirements, and operational needs.
• Build data pipelines using data from multiple data sources, PostgreSQL, AWS Grafana, AWS Quicksight, and AWS Infrastructure and associated data integration technologies.
• Design and implement secure, scalable, resilient, and cost-optimized cloud data solutions.
• Define and implement scalable data ingestion, transformation, and consumption patterns across structured and semi-structured data sources.
• Establish data engineering standards, best practices, and reusable design patterns across the Program.
• Design, develop, and optimize conceptual, logical, and physical data models supporting analytics, reporting, dashboards, and operational systems.
• Evaluate emerging technologies and recommend improvements to enhance platform capabilities and performance.
• Ensure data architecture aligns with business requirements, governance standards, and future scalability needs.
• Collaborate with analytics, reporting, and business intelligence teams to deliver high-quality data products and trusted data assets.
• Perform advanced data analysis and profiling using SQL and Python to identify trends, anomalies, and opportunities for optimization.
• Establish monitoring, alerting, observability, and automated recovery mechanisms across critical data pipelines.
• Ensure compliance with security, privacy, and regulatory requirements.
• Collaborate with Agile teams to deliver iterative business value while maintaining technical quality and delivery commitments.
• Communicate technical concepts, risks, solutions, and recommendations effectively to both technical and non-technical stakeholders.