Senior Engineer - Data Engineering

Key Responsibilities Contribute to the design and development of scalable data pipelines and a growing data lake Build and extend data processing workflows using Python, Apache Spark, and Databricks Define technical standards, best practices, and reusable frameworks for data engineering Ensure data quality, reliability, performance, and maintainability across data solutions Support data modeling, data integration, and transformation processes for analytics and reporting Drive automation, monitoring, and CI/CD improvements to ensure operational excellence Collaborate across teams, acting as a technical interface between the data platform and engineering, analytics, and business stakeholders. Contribute to architecture decisions and long-term data platform strategy Your Profile Outstanding programming experience, preferably in Python; ability to write clean, testable, production-grade code; able to write clean, testable, production-grade code Strong SQL skills and familiarity with structured and semi-structured data formats (JSON, Protobuf, Delta format) Hands-on experience with Apache Spark, ideally on Databricks, and understanding of the medallion architecture Solid grasp of data lakehouse principles, data modeling, and data governance concepts Experience building and maintaining CI/CD pipelines (e.g. GitLab CI); familiarity with IaC and deployment Cloud Platforms: Experience with AWS or comparable cloud providers; familiarity with Databricks as a managed Lakehouse platform Experience with event-driven architectures or streaming platforms (e.g. Kafka) Proven track record deploying, monitoring, and maintaining data pipelines and services in production environments; experience with testing practices Able to work autonomously and take ownership of tasks end-to-end Clear and concise communicator — comfortable working across engineering and data teams Education & experieance Bachelor's degree in Software Engineering, Mathematics, Physics, or a related field 3 years of project/coding experience in a company Cloud experience: Databricks, AWS/Azure Staging, testing, Git, pipelines Distributed systems, data pipelines Python experience: Versioning, package management, requirements/environments Change data capture Data engineering experience: SQL Partitioning Data structures (tables, relations) Lakehouse