Data Engineer

Data Engineers work collaboratively with architects, business intelligence developers, data analysts and data scientists to build and maintain analytic solutions utilizing both traditional on-premises and cloud-based platforms. The Data Engineer mid-level is a data pipeline builder contributing to the development and maintenance of data assets.


Additional Job Description:

• Designs, configures, develops, tests and deploys ELT/ETL processes and self-service reporting assets to provide data exploration capabilities to end users, while adhering to organizational, departmental, team and governmental standards and regulations.
• Proactively communicates with data consumers to improve performance of processes connecting to data. Designs and builds data models, contributing to an ongoing review of enterprise architectural standards and designs.
• Participates in data cleansing and profiling efforts and traces data quality issues to their source.
• Provides operational support for systems and applications troubleshooting and maintenance, and ad-hoc support for incidents related to data warehouses, data sets and data pipelines.
• Participates in organizational Data Governance for data assets and in enterprise-wide Agile ceremonies.
• Works with more experienced team members to capture, document and groom features and stories for Agile/scrum teams.
• Excel at working self-sufficiently in most activities and know when to engage others.
• Provides coaching to less-experienced Data Engineers.

Essential Functions:

• Designs, configures, develops, tests and deploys ELT/ETL processes across multiple sources, targets and tools, and self-service reporting assets to provide data exploration capabilities to end users.
• Demonstrates deep understanding of one or more data domains, the processes that generate the associated data, and the potential biases within those data sets.
• Leads communications with data consumers with a skill growth mindset, to improve performance of processes connecting to data, and shares best practices.
• Develops relationships and collaboration across multiple teams to deliver timely and reliable information that enables users to uncover insight from information.
• Provides operational support for systems and applications troubleshooting and maintenance support, and ad-hoc support for incidents related to data warehouses, datasets and data pipelines.
• Provides on-call support for data platforms, reporting assets, and ETL processes.
• Develops and implements data model designs, engaging less-experienced team members to grow their skills.
• Build data models, using a variety of sources and target systems, growing a better understanding on enterprise architectural standards and designs.
• Applies best practices and organizational standards of the Software Development Lifecycle, to ensure the production of high quality, reliable data assets.
• Applies the organizational standards and laws governing use of sensitive data relating to Protected Health Information (PHI) and Personally Identifiable Information (PII).
• Leads data cleansing and profiling to ensure accuracy and quality of information.
• Participates in organizational Data Governance for data asset management.
• Develops Continuous Integration and Continuous Development (CI/CD) pipelines under the guidance of more experienced team members.
• Participates in enterprise-wide Agile ceremonies determining and recommending technical programming approaches and solutions to complex applications.
• Works independently capture, document and groom features and stories for Agile/scrum teams to maximize visibility and readiness for upcoming planning and execution.
• Actively pursues opportunities to grow their business acumen and skills from more experienced team members. Provides coaching to less experienced team members.

Qualifications:

• At least five years of relevant experience developing and supporting applications, and or system development lifecycle including coding, testing, and implementation required.
• Strong Experience in Programming with Oracle SQL and PLSQL.
• Experience in Data Integration using Informatica Power Center.
• Experience in Agile/Scrum Methodologies.
• Well-versed with concepts and techniques of Business Intelligence and Data Warehousing.
• Strong written and oral communication skills with ability to interpret technical requirements.
• Excellent analytical skills to troubleshoot and resolve systems problems.
• Effective and self-sufficient in working within a diverse technology portfolio.

Preferred Qualifications:

• Experience in Healthcare Industry.
• Experience in Epic Cogito.
• Experience in Programming with Python.
• Any one or combination of these in addition to the basic qualifications
• Experience Programming in a Snowflake Data Warehouse.
• Development and Configuration Experience in Qlik Replicate or Fivetran.
• Experience in data warehouse migration from on-prem to AWS Cloud.
• Knowledge of AWS DevOps process and S3.