Qualifications
Responsibilities
Benefits
The Data Analytics Engineer 3 is responsible for designing and creating tables within data marts, data lakes and data warehouse and all related extraction, transformation and load of data functions. Work in a variety of settings to build systems that collect, manage, and convert raw data into usable information for analytics developers and business analysts to interpret. Their goal is to make data accessible so that organizations can use it to evaluate and optimize their performance. They also develop and test architectures that enable data extraction and transformation for predictive or prescriptive modeling. Data engineer will be responsible for expanding and optimizing our data and data pipeline architecture, as well as optimizing data flow and collection for cross functional teams. Takes direction and guidance from lead data engineers and department leadership to work towards enhancement of self and the team's capabilities around data and analytic competencies. Mentors junior data engineers and guides users across the organization to promote data education and a data-driven culture in all aspects of clinical and business operation
EXPERIENCE WE ARE LOOKING FOR
Deep understanding of modern data architectures, including lakehouse design patterns and scalable data processing approaches
Hands-on experience with Azure data platforms, including ADLS, Azure Data Factory (ADF), Databricks, and related lakehouse technologies
Strong experience designing and implementing metadata-driven, scalable data pipelines
Proficiency in Python and PySpark for building data pipelines, transformations, and distributed processing workloads
Experience integrating data across systems using APIs and other modern data connectivity patterns
Proficiency with DevOps and DataOps practices, including CI/CD for data pipelines and cloud infrastructure
Advanced SQL skills with experience managing and optimizing relational data platforms
Familiarity with Microsoft Fabric is a plus
Experience with healthcare data platforms such as Epic Cogito is a plus
WHAT YOU CAN EXPECT
Consultation: Work with data and analytics experts to strive for greater functionality in our data systems. Consults with data systems management teams to get a big-picture idea of the data needs.
Data Pipelines: Under the guidance of leadership, designs, implements and continuously expands data pipelines by performing extraction, transformation and loading activities. Create and maintain optimal data pipeline architecture. Assemble large, complex data sets that meet functional / non-functional business requirements. Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.
Gathers Knowledge: Gathers requirements and business process knowledge in order to transform the data in a way that’s geared towards the needs of end users.
Storage Needs: Presents data lakes, marts and warehousing options based on storage needs.
Data Architecture: Ensures that the data architecture is scalable and maintainable
Potential Issues: Investigates data to identify potential issues within ETL pipelines, notify end-users and propose adequate solutions.
Testing: Conducts preliminary testing of the warehousing and database environment before data is extracted.
Extracts Data: Extracts data and transfers it into the warehousing environment, other databases or to files.
Testing: Tests the new system once all the data has been transferred.
Maintenance: Provides maintenance and support. Maintain proper documentation and code commenting practices. Performs other duties as assigned.
QUALIFICATIONS
Required Bachelor's Degree Business, Computer Science, Engineering, Information Systems, Public Health, or related field
Preferred Master's Degree Computer Science, Business, Healthcare Management, Information Systems, or related field
5 years Building data pipelines, using ETL technologies such as SSIS or Informatica Required
3 years SQL development with SQL Server/Oracle environment Required
2 years Cloud data platforms and associated tools such as MS Azure, AWS, or GCP Required
TRAVEL IS REQUIRED:
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