Analytics Data Engineer

Corner Alliance•Washington, DC

1d•$100,000 - $120,000•Hybrid

About The Position

As an Analytics Data Engineer supporting our Federal government client, you will be trusted to provide support in making data driven decisions that improve grant program outcomes. You will work as part of a dynamic team remotely. You will work at the client site dependent on contract requirements.

Requirements

Bachelor's degree or higher in a related field, such as computer science, engineering, business analytics, information systems management, cybersecurity, engineering
6+ year’s experience in a data engineer role or related role
Experience with the design and build of scalable data pipelines to extract, transform, and load (ETL) data from various sources
Experience utilizing programming languages like Python, PySpark, and SQL to manipulate and clean data
Experience developing and implementing automation scripts to streamline data processing tasks
Experience with the deployment, configuration, and maintenance of data storage systems like data warehouses and lakes
Experience working with cloud platforms such as Azure, AWS, or GCP
US citizenship and the ability to pass public trust clearance or suitability

Nice To Haves

You can learn and grow with us.
We're looking for someone who is coachable, unflappable in navigating challenges, resourceful in learning new skills, innovative in challenging the status quo, excellent in writing, analytical in thinking, skilled in prioritization, and a rapport builder with clients and colleagues.

Responsibilities

Work with data solutions architect to establish a data platform strategy.
Provide direct technical expertise in the design, development, implementation and testing of different data pipelines.
Collaborate with team members to design, document and implement a data development life cycle to enforce consistency and uniformity of process using Databricks and cloud tooling.
Responsible for analyzing and understanding data sources, participating in requirement gathering, and providing insights and guidance on data technology and data modeling best practices.
Leverage knowledge of data models, data relationships, mapping lineage and business rules to ensure that solutions meet operational and business needs.
Implement and maintain end-to-end data pipelines and data systems in Databricks integrating CI/CD processes, continuously improving the quality of deliverables.
Establish an authoritative Lakehouse within the Analytics Platform to organize and structure data required for post-award reporting and monitoring.
Refresh and refine existing dashboarding and data analysis products (e.g., program financials, risk management, customer engagement).
Leverage advanced analytics (such as LLMs and Artificial Intelligence) to analyze unstructured program data to reduce the burden of manual review of post-award submissions, enhance ability to identify instances of fraud, waste, and abuse, and inform decision-making for effective management of project implementation.
Collaborate with business stakeholders and team members to identify automation opportunities.
Carry out our Commitments to Deliver, Grow, and Thrive.