Data Engineer

• Architect, build, and maintain scalable, reliable data pipelines (batch & streaming) to ingest, transform, and deliver data for analytics, reporting, and ML use cases.
• Architect software applications, test, and build automated tools.
• Translate complex functional and technical requirements into architecture designs and high-performing software solutions.
• Select appropriate data solution software and define hardware requirements to support performance and scalability.
• Develop and implement standards and processes for data integration projects and initiatives.
• Lead the design and development of software applications, testing, and building tools.
• Optimize SQL queries (joins, window functions, aggregations, partitioning, indexing) and data schema performance.
• Design data models, schemas, and data warehouses/data lakes (dimensional, star, snowflake schemas, normalization/denormalization).
• Ensure data quality, correctness, and consistency across datasets (validation, anomaly detection, reconciliation).
• Ensure database changes are reviewed and approved according to standards.
• Monitor, troubleshoot, and tune performance of pipelines, databases, and workloads.
• Drive adoption of engineering best practices: version control, CI/CD, testing (unit and integration for data pipelines), documentation, and code reviews.
• Collaborate with software engineers to integrate data systems into production environments.
• Provide technical assistance to junior members and to colleagues across the company.
• Mentor and coach junior and mid-level engineers, promoting engineering discipline across the team.
• Evaluate and propose new tools, frameworks, and technologies for the data platform.
• Ensure data security, governance, access control, lineage, and compliance (e.g., GDPR, CCPA, internal standards).

Senior Data Engineer

Manager, Data Engineer

Senior Data Engineer

Data Engineer

Senior Data Engineer

Junior Data Engineer