Data Engineer

IN - IDOH Data Engineer Location: Remote (Hybrid Optional)

Design and implement data modeling and data engineering solutions for complex, advanced analytical projects to perform data sourcing, data profiling, data ingestion, data manipulation, and data modeling functions.

Translate technical complexities, develop appropriate solutions, and contribute to the agency of transformation our agency into a data-driven culture.

Essential Duties/Responsibilities:

Work closely with the solution leads, project managers, data architects, data scientists, and data analysts on solution design, architecture, and implementation

Performing extraction, transformation, and loading of data from a wide variety of data sources using various data engineering tools and methods.

Designing and implementing data solutions for operational and secure integration across systems.

Assist, with guidance and oversight from data architects, in creating database models and architecture design and documentation

Conduct research and development as well as contribute to the long-term positioning of and emerging technologies related to data sourcing, cleansing, and integration

Documenting and demonstrating solutions by developing documentation, flowcharts, layouts, diagrams, charts, code comments and clear code.

Improving operations by conducting systems analysis; recommending changes in policies and procedures.

Involvement requirements gathering, solution reviews, and explaining technical complexities and business benefits in layperson terms.

Job Requirements:

Bachelor’s degree in Computer Science, Engineering or a similar field is required

3+ years of data engineering, software engineer, or similar experience

2+ hands-on industry experience working with SQL on various relational database platforms (Microsoft, Oracle, Hana, Postgres, etc.)

2+ hands-on industry experience working with enterprise ETL/DW tools like Azure Data Factory, Redshift, Informatica, etc.

Hands-on experience with aspects of data engineering design and implementation including data sourcing, data modeling of warehouses/marts/repositories, data integration/transformation/ETL, APIs, reporting, business intelligence and analytics

Hands-on experience with modern programming languages like Python, C#, JavaScript, etc.

Hands-on experience with cloud platforms like AWS, Azure, GCP, etc.

Experience with Docker for containerization and Kubernetes for orchestration a plus

Collaborative team player who is detailed oriented, focused on solution quality and execution

Progressive mindset particularly around deployment models and emerging technologies

Supervisory Responsibilities/Direct Reports:

No direct supervision responsibilities. Some oversight/guidance of staff on projects

Difficulty of Work:

Work assignments involve contributing to a wide variety of general and complex modeling and data engineering projects. The broad range of project goals requires excellent time management, analytical prowess, database querying, and data engineering design and implementation skills. Good judgement and ability to apply specialized knowledge are required to perform duties successfully. Work assignments also require critical thinking and decision-making abilities.

Responsibility:

Expected to complete project tasks independently with minimal guidance from senior staff. Work products are periodically reviewed for quality, accuracy, efficiency, and achievement of project goals by senior staff. Incumbent keeps supervisor and coworkers apprised of work.

Regularly responsible for execution of tasks that impact priorities, as well as tasks impacting specific program areas. May also contribute to projects with broader agency impact, under supervision of senior staff.

Expected to work collaboratively with other staff to make progress toward agency priorities and advancing the mission.

Personal Work Relationships:

This staff member works independently, with some support from other team members and management, to complete various modeling and data engineering projects. Maintains relationships with project teams and program area staff.

Physical Effort:

Requires sitting for long periods in front of a computer.

Working Conditions:

Work is performed indoors in a routine office environment or from an approved remote location.