Accountabilities:
Execute end-to-end data engineering activities including discovery, profiling, extraction, transformation, and loading of data from legacy systems into Azure-based environments, ensuring accuracy and consistency across migration workflows.
Design and implement ETL/ELT pipelines using modern Microsoft Azure data services, supporting structured data movement, validation, and integration across applications and reporting systems.
Perform data cleansing, normalization, and standardization to improve data quality, while conducting reconciliation checks and validation with stakeholders to confirm migration completeness.
Support data governance and documentation efforts by defining data standards, transformation logic, and maintaining technical artifacts for ongoing system reliability and compliance.
Collaborate with application and analytics teams to coordinate migration timelines, enable data availability for production systems, and support reporting solutions such as Power BI dashboards.
Requirements:
5+ years of experience in data engineering, ETL development, or data migration, with strong hands-on SQL expertise and deep understanding of relational data modeling.
Proven experience working with data cleansing, validation, and large-scale data migration projects from legacy systems into modern cloud environments.
Strong proficiency with Microsoft Azure data services, including Azure Data Factory and Synapse, ideally within Azure Government Cloud environments.
Experience with Microsoft Dataverse, including table structures, relationships, and data modeling concepts for enterprise applications.
Familiarity with API-based data integration patterns, data governance principles, and analytics/reporting tools such as Power BI is highly valued.
Ability to work independently while collaborating effectively with cross-functional technical teams in structured, delivery-focused environments.
U.S. citizenship and eligibility for Public Trust clearance required.
Benefits:
Competitive compensation aligned with experience and market standards
Fully remote work arrangement within the United States
Opportunity to work on high-impact federal and enterprise data modernization programs
Exposure to advanced Microsoft Azure and cloud data technologies
Collaborative, mission-driven technical environment focused on innovation and modernization
Professional growth in data engineering, cloud architecture, and enterprise analytics
Equal opportunity workplace committed to diversity, inclusion, and fair hiring practices
How Jobgether works:
We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.
We appreciate your interest and wish you the best!
Why Apply Through Jobgether?
Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.
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