ABOUT THE JOB

Loopback is seeking an innovative and team-oriented Data Integration Engineer to join our dynamic team. In this role, you will be responsible for building and maintaining data transformation mappings from source to destination formats. You will play a critical role in managing data flow processes, analyzing data, and collaborating with cross-functional teams to identify and implement system and process improvements. Additionally, you will design, document, implement, and support key clinical datasets.

REQUIREMENTS

You will thrive if you:

• Exhibit a “self-starter” mindset in taking ownership over delegated responsibilities
• Have excellent program/task organizational skills
• Are detail and results oriented

You bring a toolkit of your past experiences of:

• 3-5 Years of experience as a Data Integration Engineer or similar role
• Implementing and designing data curation, and data analysis
• Orchestrating data transformation through cloud native analytics platforms (Snowflake, Databricks) across cloud environments (Azure, AWS, GCP)
• Building and modeling data in relational and non-relational data storage technologies including schema design, stored procedure development and performance and optimization techniques (e.g. SQL & NoSQL, C#, Python, etc.)
• Effective collaboration, experienced in creating technical partnerships across teams
• Learning and understanding the various technical domains across the enterprise and able to communicate complex technical and business concepts across the enterprise and various business stakeholders
• Effectively delivering results in a fast-paced environment while managing multiple priorities
• Documenting and testing your designed solutions, engaging with QA and DevOps teams

· Manage evolving data ingestion formats across Health Systems, Life Science, and Enterprise Partner environments.

• Own and maintain the codebase and documentation for data transformations from source systems into existing data pipelines.
• Develop and sequence jobs and processes to load, transform, and manage data within the data lake and data warehouse.
• Maintain and enhance the Loopback data model, ensuring codebase reliability to meet client/application SLA requirements.
• Design and implement scalable, reliable data engineering pipelines to process large datasets across diverse sources and analytics use cases.
• Drive internal process improvements by automating manual tasks and optimizing data delivery pipelines.
• Identify and implement solutions to improve data reliability, efficiency, and quality.
• Develop, promote, and enforce best practices in data integration and engineering.
• Collaborate with business stakeholders to understand use cases, capture business rules, and align on solutions that address business challenges.
• Conduct data profiling, create documentation, and develop automated tests to ensure data quality and accuracy.