Role Description GDIT’s DOJ/OJP team is looking for a dynamic and experienced ETL Developer to join our Agile teams. Our client is engaging in a significant overhaul of its legacy IT environment and approach. You, as the ETL Developer, will play a pivotal role in the planning and execution of this modernization effort. While working closely with senior Federal staff, Data Architects, and the Business Analysts, you will design and implement ETL processes to support migration of legacy data to a redesigned modern application. Qualifications - 6+ years of related experience - US Citizenship Required: Yes - Skills: Data Architecture, Data Requirements, Data Solutions - Certifications: None Requirements - Design and implement industry best ETL technologies to satisfy client requirements. - Design and develop optimal code to maintain exceptional performance in processing large volumes of data. - Translate business requirements into technical specifications. - Design, develop, and test ETL solutions and automate data loading processes. - Establish ETL environments according to project requirements. - Develop and implement an efficient migration process to move ETL objects from development to test and production environments. - Support the project team throughout the design, development, and testing process. - Participate in all design reviews and requirement sessions, as required. - Support project documentation, as required. - Understand database design, programming concepts, data modeling, and framework management. - Communicate ideas to both technical and non-technical people at all levels of the organization. - Work with Business Analysts, Data Architects, Enterprise Architects, and ETL Architects to ensure business requirements are being met with the solution being developed. - Identify and reuse ETL components and services to avoid duplicative implementations. - Mentor other team members in developing, documenting, and modifying ETL components. - Develop advanced and complex ETL processes in the AWS GovCloud using tools such as AWS Glue, S3, Python, Spark, SQL, Athena. - Support and administer the MySQL database in the migration environment on the cloud. Benefits - Medical plan options, some with Health Savings Accounts. - Dental plan options. - Vision plan. - 401(k) plan with pre and post-tax contribution options and company match. - Full flex work weeks where possible. - Variety of paid time off plans including vacation, sick and personal time, holidays, paid parental, military, bereavement, and jury duty leave. - 15 days of paid leave per calendar year for vacations, personal business, and illness. - 10 paid holidays per year. - Paid Family Leave program providing up to 160 hours of paid leave in a rolling 12-month period for eligible employees. - Short and long-term disability benefits, life, accidental death and dismemberment, personal accident, critical illness, and business travel and accident insurance.

• Work through accounting data migrations under supervision — extract, clean, transform, and validate financial data. • Learn and work with Zoho Books, Zoho Creator, and DataBridge migration workflows. • Write and adapt Python scripts for data extraction and transformation tasks. • Validate migrated data against source trial balances — accuracy is non-negotiable. • Document migration patterns and edge cases to feed into the DataBridge product roadmap.

• As a Procurement Data Analyst at kiresult, you are responsible for converting procurement data into actionable insights that support our clients' strategic sourcing initiatives. • You will work directly with our clients to understand their needs and bring clarity and transparency to their procurement spend. • You will take full ownership of implementing our SaaS solution for new clients and ensure customer success. • Extract, clean, and transform large datasets using Excel and Python to enable timely and accurate analyses. • Identify opportunities for cost savings, supply chain improvements, and other procurement efficiency gains. • Support clients in interpreting analysis results and guide them toward data-driven decision-making.

• Take ownership, improve, scale, and iterate on existing data processing pipelines. • Design and implement new data processing pipelines. • Collect and monitor performance metrics. • Play a key role in discussing and implementing security best practices.