Data Engineer
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Job Description
Data Engineer responsible for designing, building, and maintaining data pipelines at Loopback Health. Collaborating with cross-functional teams to drive system and process improvements.
Responsibilities:
- Design, build, and maintain scalable data pipelines to ingest, transform, and deliver data across diverse sources and environments
- Develop and manage ETL/ELT processes within cloud-based data platforms (e.g., Snowflake, Databricks)
- Own and maintain data transformation logic, codebases, and supporting documentation
- Model and optimize data structures within data lakes and data warehouses to support analytics and reporting use cases
- Ensure data reliability, integrity, and performance to meet client and application SLA requirements
- Manage evolving data ingestion formats across Health Systems, Life Sciences, and Enterprise partner ecosystems
- Drive automation and continuous improvement of data workflows to reduce manual effort and increase efficiency
- Implement data quality checks, monitoring, and validation processes
- Collaborate with business and technical stakeholders to gather requirements and translate them into scalable data solutions
- Develop and promote best practices in data engineering, data modeling, and pipeline design
- Conduct data profiling and support testing efforts in partnership with QA and DevOps teams
Requirements:
- 3–5 years of experience in Data Engineering, Data Integration, or a related field
- Experience designing and building data pipelines and transformation workflows
- Hands-on experience with cloud data platforms (Snowflake, Databricks) and cloud environments (Azure)
- Strong experience with SQL and at least one programming language (e.g., Python, C#)
- Experience with relational and non-relational data modeling, schema design, and performance optimization
- Familiarity with data lake and data warehouse architecture
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