Data Engineer

• Job ID:

J54067

• Job Title:

Data Engineer

• Location:

Dallas, TX

• Duration:

10 Months + Extension

• Domain Exposure:

Consumer Staples

• Client:

To Be Discussed Later

• Employment Type:

W-2, 1099, C2C

• Work Authorization:

US Citizen, Green Card, H-1B, OPT-EAD, CPT, Other

Job Title: Data Engineer

Location: Dallas, TX

Duration: 8 Months + Extension

Bill Rate: $76/hour (C2C)

Job Type: W-2, 1099, C2C

Client: To Be Discussed Later

Work Authorization: US Citizen, Green Card, OPT-EAD, CPT, H-1B, H4-EAD, Other

Job Description:

Data Engineer to transform complex data into trusted, usable information to support program delivery and operational improvements. The candidate will understand policy-relevant research questions, evaluate available data sources, and develop analytics products to deliver actionable insights.

Design and build data pipelines, integrate and transform data from multiple sources, identify and address data quality issues, and establish controls to support responsible use of data. This role requires both technical depth and strong analytical judgment, including the ability to work with large, complex, and confidential datasets.

The successful candidate must be self-directed and comfortable supporting the data needs of multiple teams, systems, and products. They must also be comfortable supporting data conversions associated with system modernization and/or replacement efforts. The right candidate will be excited by the prospect of optimizing the Commonwealth's longitudinal data architecture to support its next generation of data initiatives.

Roles and Responsibilities:

• Create and maintain optimal data pipeline architecture.
• Design and implement cloud-based data solutions using AWS services such as S3, Glue, Redshift, EMR, Athena, Kinesis, and Lambda.
• Build and maintain data orchestration workflows using tools such as Apache Airflow, AWS Step Functions, or similar services.
• Assemble large, complex datasets that meet functional and non-functional business area requirements.
• Engineer analytical data environments that support advanced statistical analysis, predictive modeling, machine learning, and evidence-building activities.
• Partner with data scientists, research analysts, and policy analysts to ensure enterprise data assets support reproducible research and statistical modeling.
• Identify, design, and implement internal process improvements, including automating manual processes, optimizing data delivery, and redesigning infrastructure for greater scalability.
• Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and big data technologies.

Equal Opportunity

Employer

We are an equal opportunity employer. All aspects of employment including the decision to hire, promote, discipline, or discharge, will be based on merit, competence, performance, and business needs.

We do not discriminate on the basis of race, color, religion, marital status, age, national origin, ancestry, physical or mental disability, medical condition, pregnancy, genetic information, gender, sexual orientation, gender identity or expression, national origin, citizenship/ immigration status, veteran status, or any other status protected under federal, state, or local law.