Build and operate reliable data integrations and data platform capabilities
Create new source ingestions feeds and interfaces
Maintain and troubleshoot existing interfaces
Improve ingestion, validation, and monitoring
Partner with stakeholders to deliver analytics, warehousing, and reporting solutions
Automate environments and standardize deployments
Improve observability and reliability for data services
Implement changes and enhancements in internal flat file and message processing services
Communicate with clients and their technical stakeholders
Aid in the development and design of analytics projects
Discover opportunities for improvement through data analytics
Maintain documentation related to datasets and analysis
Apply generative AI in engineering work

3 to 5 Years experience
Bachelor's Degree or Equivalent Experience in Computer Science
2+ years of coding experience with Microsoft SQL
1+ years working with big data technologies including Databricks, Apache Spark, Python, Microsoft Azure (Data Factory, Dataflows, Azure Functions, Azure Service Bus)
Understanding of engineering fundamentals: testing automation, code reviews, telemetry, iterative delivery and DevOps
Experience with polyglot storage architectures including relational, columnar, key-value, graph or equivalent
Some experience with BI tools, preferably Power BI
Familiarity with operational excellence practices such as incident response and runbooks
Understanding of security fundamentals for cloud platforms (identity and access management, secrets management, encryption, and audit logging)
Experience packaging and running services using containers and orchestration (e.g., Docker, Kubernetes) and/or serverless patterns
Experience with CI/CD, version control, and release automation for data pipelines and platform components (e.g., Azure DevOps/GitHub Actions)

Data Engineer

Key skills