Lead Data Engineer

Analytical Mechanics Associates (AMA) is hiring a full-time Lead Data Engineer for a California hybrid role. In this position, you will help shape analytics product design, modernize data pipelines, and deliver governed reporting experiences that support both operational teams and executive stakeholders. The team works in an agile, hybrid environment aligned to the Central Time Zone .

What you'll deliver

• Analytics product design leadership, including dashboard layouts , visualization approach , and semantic model architecture .
• Production-grade reports and dashboards , including direct stakeholder engagement and KPI validation .
• Power BI semantic models for executive dashboards and operational reporting, enabling governed self-service analytics .
• Data pipelines built with Databricks , Azure Data Factory , and/or Snowflake using a structured layered architecture: Raw , Transformed , and Analytics .
• Automated data quality checks , reconciliation, pipeline monitoring, alerts, and operational support dashboards.
• Modernization of legacy workloads by reverse-engineering and transforming SQL , SSIS , or integration processes into maintainable patterns.
• Enterprise-grade data governance covering column-level documentation , role‑based access controls , standardized metric definitions , and full data lineage traceability .

How you'll work with the team

• Partner with business leaders to translate operational and analytical needs into scalable technical solutions.
• Provide technical direction across two primary work streams: data environment and data presentation .
• Mentor team members and help establish a consistent, collaborative engineering culture.
• Troubleshoot technical issues and proactively detect data issues using automated validation and monitoring.

Core requirements

• BA/BS in a technical field (including mathematics, information technology, engineering, accounting, or computational finance).
• 5+ years of professional experience in business analytics or data engineering, including 5+ years hands‑on 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 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 Data Vault 2.0 or another governed historical modeling approach.
• Ability to communicate effectively with technical teams and non‑technical stakeholders.
• Demonstrated ownership from design through production support.
• Strong documentation, troubleshooting, and problem‑solving skills.
• Must have a primary place of business in the Central Time Zone .

Tools you'll use

• Power BI , Tableau , DOMO , Databricks , Azure Data Factory , Snowflake
• SQL , Python , SSIS
• Azure DevOps , CI/CD , Git
• Data Vault 2.0 , DAX

Preferred 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.

Compensation: USD 130,000 - 155,000 per year.