Optum - Data Engineering Consultant - Python/SQL/ETL

As a Data Engineering Consultant, you will be responsible for architecting and implementing robust data solutions that support the Data Science teams analytical and modeling efforts. You will work closely with Data Scientists, Analysts, and cross-functional teams to ensure seamless data access, processing, and integration. Your expertise in Python, SQL, ETL, Big Data technologies, reporting, and cloud platforms will be pivotal in advancing our data-driven healthcare initiatives.

Key Responsibilities :

Data Pipeline Development and Management :

- Build scalable data workflows to process large volumes of structured and unstructured data using Python and pandas.

Database and Data Warehouse Management :

- Collaborate on data modeling and schema design to optimize query performance and storage efficiency.

Big Data and Cloud Infrastructure :

- Leverage cloud platforms (e.g., AWS, Azure, Google Cloud) to design and manage data storage, processing, and integration solutions.

Reporting and Data Accessibility :

- Ensure data accessibility and security for stakeholders while maintaining compliance with healthcare regulations.

Collaboration and Cross-Functional Support :

- Work with Product Owners and business stakeholders to understand data requirements and translate them into technical solutions.

Healthcare Data Expertise :

- Ensure compliance with healthcare data privacy regulations such as HIPAA and HITECH Act.

Required Skills and Experience :

- 6 to 10 years of professional experience in Data Engineering or related roles.

- Proficiency in Python and pandas for data manipulation and processing.

- Strong expertise in SQL for querying, database design, and optimization.

- Solid experience building ETL pipelines and integrating data from multiple sources.

- Hands-on experience with Big Data technologies (e.g., Hadoop, Spark, Hive, etc.).

- Familiarity with reporting tools (e.g., Tableau, Power BI) and data visualization workflows.

- Experience with cloud platforms (e.g., AWS, Azure, Google Cloud), including data storage and processing services.

- Knowledge of data governance, security, and compliance, particularly in healthcare environments.

Preferred Qualifications :

- Exposure to healthcare data formats (e.g., HL7, FHIR) and standards.

- Experience with containerization and orchestration tools (e.g., Docker, Kubernetes).

- Basic understanding of machine learning workflows and how data engineering supports them.

- Familiarity with version control systems (e.g., Git) and Agile methodologies.

Soft Skills :

- Strong problem-solving and analytical skills.

- Excellent communication and collaboration abilities across technical and non-technical teams.

- Attention to detail and commitment to delivering high-quality data solutions.

- Ability to thrive in a fast-paced, dynamic environment.

Education :

- Bachelors or Masters degree in Computer Science, Data Engineering, Information Systems, or a related field.