Title: Azure Data Engineer

Location: Minneapolis, MN

Duration: 12 Months

Job Description:

Description:

Support the full data engineering lifecycle including research, proof of concepts, design, development, testing, deployment, and maintenance of data management solutions

Utilize knowledge of various data management technologies to drive data engineering projects

Lead data acquisition efforts to gather data from various structured or semi-structured source systems of record to hydrate client data warehouse and power analytics across numerous health care domains

Leverage combination of ETL/ELT methodologies to pull complex relational and dimensional data to support loading DataMart s and reporting aggregates.

Eliminate unwarranted complexity and unneeded interdependencies

Detect data quality issues, identify root causes, implement fixes, and manage data audits to mitigate data challenges

Implement, modify, and maintain data integration efforts that improve data efficiency, reliability, and value

Leverage and facilitate the evolution of best practices for data acquisition, transformation, storage, and aggregation that solve current challenges and reduce the risk of future challenges

Effectively create data transformations that address business requirements and other constraints

Partner with the broader analytics organization to make recommendations for changes to data systems and the architecture of data platforms

Support the implementation of a modern data framework that facilitates business intelligence reporting and advanced analytics

Prepare high level design documents and detailed technical design documents with best practices to enable efficient data ingestion, transformation and data movement.

Leverage DevOps tools to enable code versioning and code deployment.

Leverage data pipeline monitoring tools to detect data integrity issues before they result into user visible outages or data quality issues

Leverage processes and diagnostics tools to troubleshoot, maintain and optimize solutions and respond to customer and production issues

Continuously support technical debt reduction, process transformation, and overall optimization

Leverage and contribute to the evolution of standards for high quality documentation of data definitions, transformations, and processes to ensure data transparency, governance, and security

Ensure that all solutions meet the business needs and requirements for security, scalability, and reliability