Data Engineer at HyerTek

Rockville, Maryland, United States -

Full Time

Start Date

Immediate

Expiry Date

17 May, 26

Salary

140000.0

Posted On

16 Feb, 26

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Data Cleansing, Data Visualization, Data Migration, Data Operationalization, Source Data Mapping, ETL/ELT Pipelines, Azure Data Factory, Dataflows, Dataverse SDK, Power BI, Microsoft Fabric, Data Lakehouse, Dynamics 365, SQL, Python, PowerShell

Industry

IT Services and IT Consulting

Description

Description HyerTek is a fast-moving Microsoft solutions partner seeking a data engineer to support the full data engineering lifecycle — from cleansing to visualization. You'll work directly with our solutions team and client end users to migrate and operationalize data for public sector, defense, and commercial programs. That starts with assessing client environments and mapping source data — whether it's legacy spreadsheets, flat files, or disconnected databases. From there, you'll build extraction and transformation pipelines to cleanse, normalize, and load that data into production systems across Dataverse, Azure SQL, and SharePoint. Once the data is governed and operational, you'll build the reporting and visualization layer—standing up Power BI dashboards, Fabric Lakehouses, and consolidated views that turn raw data into decision-ready insights. Requirements • Migrate data from legacy data systems, Excel workbooks, SharePoint, and Access databases into Dataverse and Azure data stores • Build and maintain ETL/ELT pipelines using Azure Data Factory, Dataflows, Dataverse SDK, or whatever fits the problem • Design and build Power BI reports and dashboards that support operational decision-making at the command level • Work with Microsoft Fabric for data lakehouse architecture, data integration, and consolidated analytics • Model and manage data within Dynamics 365 / Dataverse, including entity design, relationships, and data quality • Transform messy, inconsistent source data into clean, governed datasets—Excel normalization, deduplication, validation • Connect data across Power Platform apps, Power Automate flows, and Power BI for end-to-end visibility • Work in Azure Government (GCC High / IL4-IL5) environments • Document data flows, mappings, and BI solutions so the team can maintain and scale them WHAT YOU'LL NEED Eligibility for an Active Secret clearance. You must be a U.S. citizenship 3+ years working across the Microsoft data stack—you don’t need to be an expert in all of it, but you need real experience with most of: Azure data services, D365/Dataverse, Power BI, Power Platform, and Excel-based data work Hands-on Power BI experience: data modeling, DAX, building reports and dashboards that stakeholders actually use Experience migrating or integrating data into Dataverse or D365 (beyond simple imports—you’ve dealt with referential integrity, transformations, and data quality) Solid SQL skills Scripting ability in Python, PowerShell, or M (Power Query) Prior work in DoD or federal IT environments Clearance & Work Authorization This position requires U.S. citizenship and the ability to successfully obtain and maintain a U.S. Department of Defense (DoD) clearance. Candidates must be authorized to work in the United States without the need for employment-based visa sponsorship now or in the future. HyerTek will not sponsor applicants for U.S. work visa status for this opportunity, and no sponsorship is available for H-1B, L-1, TN, O-1, E-3, H-1B1, F-1, J-1, OPT, CPT, or any other employment-based visa. Salary Range $120,000 – $140,000 annually, depending on experience, technical depth, and clearance status. Equal Employment Opportunity (EEO) HyerTek is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status, age, or any other protected status.

Responsibilities

The Data Engineer will support the full data engineering lifecycle, including cleansing and visualization, by migrating and operationalizing data for public sector, defense, and commercial programs. This involves assessing client environments, mapping source data, and building extraction and transformation pipelines to load data into production systems like Dataverse, Azure SQL, and SharePoint.