Job description
As a Data Engineer on the Data Architecture team, you will play a key role in technology initiatives to advance health informatics and analytics in the health sciences by advancing the usability, performance, and overall architecture of the Data Infrastructure. You will develop fastest, reliable, and large-scale data processing pipelines to ingest data from multiple data sources into Enterprise Data warehouse and Data Lake. Involves technical acumen for planning, designing, developing, implementing, and administering data-based systems that acquire, prepare, store, and provide access to data and metadata. Maintains and optimizes systems and migrates data and systems as needed. Ensures integrity and completeness of data and workflow, manages and / or develops data practices, databases, and information systems as well as guidelines, dictionaries, registries and / or services. May include interpretation of scientific research data artifacts as well as mediation across science and technology domains and long-term data care. As information architect and data steward, designs systems, data products and / or data production processes while focusing on data curation, data exchange, data security, data integrity and information environments. (Re)evaluates frameworks, strategies, standards, and standards-making activities. May involve work with a project-level data repository, a center, or an archive. This role will require you to be on-site once a month.
• Minimum five years of software development experience. • Development experience on the data processing side of software development. • Strong industry experience in programming languages such as Python or C#, with the ability to pick up new languages and technologies quickly. • Experience with Orchestration tools like Airflow or SSIS is required. • Working knowledge of Linux/Unix operating systems. • Strong experience with Relational like SQL Server or Oracle is required. • Experience designing and delivering solutions utilizing distributed systems like Spark is preferred. • Strong background in Data warehousing and ETL principles, architecture, and its implementation in large environments. • Working knowledge of leading cloud platforms like Azure, AWS, and GCP; Microsoft Azure experience is preferred. • Healthcare experience is strongly preferred but not required. • Bachelor’s degree in computer science, Computer Engineering, or related field from an accredited college or university; Master’s Degree preferred.
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