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Popular mid-level data role, metro location, broad skillset, and known SaaS employer.
Core data engineering is transferable, but Databricks, Azure, and governance requirements increase domain specificity.
Explicit 5+ years plus mandatory big-data, cloud, and programming skills required.
Design, develop and operate large-scale, high performance data structures and pipelines for data-powered products and data science.
Implement distributed, scalable data ingestion, movement, transformation, and aggregation pipelines integrating multiple data sources.
Mentor junior engineers, contribute to code repositories, enforce coding standards, and participate in product design and agile delivery processes.
5+ years of data engineering experience.
Experience with big data technologies such as Spark, Databricks, Delta Lakes, Hive.
4+ years experience in core languages like Python, Scala, or Java (Python preferred).
Hands-on experience with public cloud PaaS offerings, preferably Azure.
Experienced in building batch processing and real-time streaming big data pipelines using distributed computing frameworks.
Familiar with TDD, CI/CD (preferably Azure DevOps), and unit/integration testing for high-quality production code.
Knowledgeable in data security, authentication, governance, privacy, and architectural data security approaches within complex data environments.