Data Engineer

Job Summary and Qualifications

As a consulting Data Engineer, you will be part of the Automation community which includes data platforms, data warehousing, software engineering, and visual insights. We use our data infrastructure to power analytics and data products and to deliver relevant experiences in near real-time.

In this role you will:

• Work with data engineers, data architects, data scientists, and other internal stakeholders to understand product requirements and then design, build, and monitor data platforms and pipelines that meet today's requirements but can gracefully scale.
• Implement automated workflows that lower manual/operational costs, define and uphold SLAs for timely delivery of data, and move the company closer to democratizing data.
• Enable a self-service data architecture supporting query exploration, dashboards, data catalog, and rich data discovery.
• Promote a collaborative team environment that prioritizes effective communication, team member growth, and success of the team over success of the individual.
• Design and create real-time data pipelines that accelerate the time from idea to insight.
• Adheres to and supports data engineering best practices, processes, and standards.
• Produce high quality, modular, reusable code that incorporates best practices and serves as an example for less experienced engineers.
• Helps promote and support data security best practices that align with industry standards and regulatory and legal requirements.
• Supports data analysis efforts and solution proposals to data related and data architecture problems.
• Supports implementation of unit and integration tests and promotes and conduct performance testing where appropriate.

Qualifications:

• 6+ years in a data engineering, data architecture, or related roles
• Google Cloud Certified Professional Data Engineer, Microsoft Certified: Azure Data Engineer, or AWS Certified Data Analytics Certified.
• Strong knowledge of public cloud best practices and design patterns used in creating, automating, and supporting data pipelines.
• Experience assembling large, complex sets of data that meet functional and non-functional product requirements.
• Experience identifying, designing, and implementing internal process improvements including redesigning data platforms for greater scalability, optimized data delivery, and automating manual processes.
• Experience and use analytical tools to monitor data pipeline metrics and provide actionable intelligence to increase operational efficiency and valuable data outcomes.

Experience with the following technologies:

• ETL Tools such as SSIS and Visual Studio
• Design and Build SSIS packages
• SQL writing complex queries views and stored procedures
• SSIS ETL using SQL, Stored procedures and script tasks
• Python
• SQL best practices.
• Git/GitHub.
• CI/CD automation tools.
• SQL and analytical data warehouses
• Agile methodologies and how to apply Agile within the team.

Preferred

• Experience Meditech NPR report Plus
• Experience Open Gate Plus
• Experience FHIR.