Lead Data Engineer
Manager
Analytics
Azure DevOps
Big Data
Business Analytics
Business Intelligence
Cloud Data Warehouse
Cloud Platform
Data
Data Analysis
Data Analytics
Data Architecture
Data Engineer
Data Governance
Data Integration
Data Management
Data Pipeline
Data Platform
Data Processing
Data Quality
Data Security
Data Vault
Data Visualization
Data Warehouse
Database
Databases
DevOps
Devops Tools
Digital Marketing
ETL
Hr Technology
Informatica
Integration
Management
Microsoft
Power BI
Power Platform
Project Management
Reporting and Analytics
Software Development
SQL
Visual Design
Job Description
Analytical Mechanics Associates (AMA) is hiring a full-time Lead Data Engineer in California (hybrid) to help design and modernize analytics capabilities end to end. This role focuses on building production-ready reporting, governed data pipelines, and enterprise data governance while mentoring a team in an agile hybrid environment aligned with the Central Time Zone. The salary range is USD 130,000 - 155,000 per year.
What you’ll do
- Lead analytics product design, including dashboard layouts, visualization approaches, and semantic model architecture.
- Design and deliver production-grade reports and dashboards, working directly with stakeholders to validate KPIs.
- Build certified Power BI semantic models, including executive dashboards, operational reporting, and governed self-service analytics.
- Design and implement data pipelines using Databricks, Azure Data Factory, or Snowflake, using a 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 engineering standards across SQL, Python, notebooks, repositories, testing, documentation, and naming conventions.
- Implement Azure DevOps branching, CI/CD, release management, and environment separation.
- Define enterprise data governance practices, including column-level documentation, role-based access controls, standardized metric definitions, and end-to-end data lineage traceability.
- Translate operational and analytical needs into scalable solutions by partnering with business leaders.
- Support technical direction for two primary work streams: data environment and data presentation.
- Mentor team members and help maintain a consistent, collaborative engineering culture.
- Troubleshoot technical issues and proactively detect data problems through automated validation and monitoring.
What you bring
- 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 at least 5 years hands-on work with BI visualization tools such as Power BI, Tableau, DOMO, or equivalent platforms.
- Production experience with Databricks, Snowflake, Azure Data Factory, or a comparable modern cloud data platform.
- Advanced skills in SQL and Python, plus 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 both technical teams and non-technical business stakeholders.
- Demonstrated ownership from design through production support, with 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
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.
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