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Lead Data Engineer

$130k - $155k
Full-time

Analytical Mechanics Associates

Job Description:

Analytical Mechanics Associates (AMA) is seeking a full-time Lead Data Engineer with deep experience in data engineering, reporting, analytics, and end-to-end data platform development. The qualified candidate will join a hybrid project team (Central Time Zone) supporting dashboard development, data pipeline modernization, and governed analytics delivery in an agile environment.


Responsibilities:

  • Brainstorm and lead analytics product design including dashboard layouts, visualization approaches, and semantic model architecture.
  • Design and develop production-grade reports and dashboards, including direct stakeholder engagement and KPI validation.
  • Build certified Power BI semantic models, executive dashboards, operational reporting, and governed self-service analytics.
  • Design and implement data pipelines using tools such as Databricks, Azure Data Factory, or Snowflake, following a structured layered architecture (Raw, Transformed, Analytics).
  • Implement automated data quality checks, reconciliation, pipeline monitoring, alerts, and operational support dashboards.
  • Reverse-engineer and modernize legacy SQL, SSIS, or integration workloads into maintainable modern patterns.
  • Establish and enforce engineering standards for SQL, Python, notebooks, repositories, testing, documentation, and naming conventions.
  • Implement Azure DevOps branching strategies, CI/CD pipelines, release management, and environment separation.
  • Design enterprise data governance frameworks including column-level documentation, role-based access controls, standardized metric definitions, and full data lineage traceability.
  • Partner with business leaders and stakeholders to translate operational and analytical needs into scalable technical solutions.
  • Assist in the technical direction of the overall project team covering two primary work streams: data environment and data presentation.
  • Mentor team members and help establish a consistent, collaborative engineering culture.
  • Help troubleshoot and overcome technical issues, proactively detecting data issues through automated validation and monitoring.

Required Qualifications:

  • BA/BS in a technical field including but not limited to mathematics, information technology, engineering, accounting, or computational finance.
  • 5 plus years of professional experience in business analytics or data engineering, with a minimum of 5 years of hands-on experience with BI visualization tools such as Power BI, Tableau, DOMO or equivalent platforms.
  • Strong production experience with Databricks, Snowflake, Azure Data Factory, or a comparable modern cloud data platform.
  • Advanced SQL and Python skills.
  • Experience building production ingestion, transformation, and analytics pipelines.
  • Experience implementing data governance, quality monitoring, lineage, and access controls.
  • Experience reverse-engineering and modernizing legacy SQL, SSIS, or integration workloads.
  • Experience with Git, Azure DevOps, CI/CD, testing, and controlled production releases.
  • Experience with Databricks, Snowflake, Azure Data Factory, or a comparable modern cloud data platform.
  • Experience with Data Vault 2.0 or another governed historical modeling approach.
  • Ability to communicate effectively with both technical teams and non-technical business stakeholders.
  • Demonstrated ownership of solutions from design through production support.
  • Strong documentation, troubleshooting, and problem-solving skills.
  • Must have a primary place of business in the Central Time Zone.

Desired Qualifications:

  • Certification in data visualization with Power BI.
  • Experience with Microsoft Fabric Lakehouse, Warehouse, Data Pipelines, Dataflow Gen2, DirectLake, and semantic models.
  • Experience with Spark, Delta Lake, dbt, or dbt-fabric.
  • Proficiency in DAX, Tableau, or other BI visualization tools.
  • Experience with API integrations, vendor-file automation, and workflow automation.
  • Experience with AWS-based data services (Lambda, S3, Glue, Athena).
  • Familiarity with Azure Key Vault, service principals, managed identities, and Microsoft Purview.
  • Experience setting technical standards and mentoring engineers or analysts.
  • Master's degree in Data Science, Applied Mathematics, or a related field.

Salary range: $130k-$155k

Candidates must be US citizens or Permanent Residents

Analytical Mechanics Associates (AMA) is proud of our customer relationships, our diverse and dynamic work environment, and our employees' career satisfaction. AMA is a small business with a wide reach; headquartered in Hampton, VA, AMA has operations in Greenbelt, MD; Huntsville, AL; Dallas and Houston, TX; Denver, CO; Mountain View, CA; and Edwards Air Force Base, CA. With over 60 years of experience, AMA specializes in aerospace engineering, science, analytics, information technology, and visualization solutions. AMA combines the best of engineering, science, and mathematics capabilities with the latest in information technologies, visualization, and multimedia to build creative solutions. We offer competitive salaries and a substantial benefits package, including but not limited to paid personal and federally recognized holiday leave, salary deferrals into a 401(k)-matching plan with immediate vesting, tuition reimbursement, short/long term disability plans, and a variety of medical, dental, and vision insurance options.

AMA is committed to the professional growth of every employee, understanding that the successes of our employees drive our success. We provide a work environment that is engaging, collaborative, and supportive. To learn more about our company, please visit our website at and follow us on Facebook and LinkedIn.

AMA is an Equal Opportunity Employer and does not discriminate against any applicant for employment or employee because of race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, protected veteran status, or any other characteristic prohibited under federal, state, or local laws.

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