The Data Engineer leads the design, development, and maintenance of scalable and secure data architecture, pipelines, and systems to support the company鈥檚 data-driven initiatives. This role not only ensures the integrity, performance, and delivery of data solutions but also guides the broader data engineering team, mentors junior engineers, and drives innovation and best practices. The Data Engineer collaborates cross-functionally to align data solutions with strategic business goals and plays a critical role in shaping the company鈥檚 data infrastructure roadmap.
Responsibilities:
- Design, build, and scale robust ETL pipelines to support complex data workflows while ensuring high performance, reliability, and adaptability to evolving business needs.
- Automate and manage data ingestion from diverse sources (databases, APIs, cloud platforms), ensuring system resilience, fault tolerance, and failover readiness.
- Optimize data storage, processing, and retrieval layers to balance performance, scalability, and cost efficiency across the data platform.
- Modernize and enhance legacy data systems by identifying gaps, implementing architectural improvements, and aligning solutions with future business requirements.
- Lead technical excellence within the data engineering function through mentorship, code reviews, best-practice enforcement, and adoption of advanced tools and frameworks.
- Ensure end-to-end data quality, integrity, and governance by implementing validation, monitoring, testing, and compliance-focused data controls.
- Collaborate cross-functionally with analytics, product, engineering, DevOps, and business stakeholders to translate requirements into scalable data models and transformations.
- Drive a data-driven culture and long-term data strategy by enabling self-service analytics, maintaining clear documentation, leading training initiatives, and contributing to architecture roadmaps and governance policies.