Data Engineer/Analytics Developer (End-to-End ETL & BI) - Hybrid Baltimore, Maryland

Responsibilities:

• Create interactive reports, KPIs, and executive dashboards in Microsoft Power BI.
• Develop data ingestion frameworks to extract data from enterprise applications, APIs, flat files, databases, and legacy systems.
• Perform data cleansing, transformation, and integration using Spark, SQL, notebooks, and orchestration pipelines.
• Design and implement end-to-end ETL/ELT pipelines for structured and unstructured data from multiple source systems.
• Create and manage medallion architecture (bronze, silver, gold layers) for scalable analytics solutions.
• Build and optimize data warehouses, lakehouses, and semantic models for reporting.
• Develop reusable notebooks, pipelines, and workflows in Azure Synapse Analytics / Databricks.
• Implement data quality checks, logging, error handling, and monitoring across data pipelines.
• Collaborate with business stakeholders to gather requirements and translate them into technical solutions.
• Optimize performance of SQL queries, Spark jobs, and Power BI datasets.
• Support governance, security, and access controls for enterprise data platforms.

Minimum Qualifications:

• Seven years' experience as an Engineer and/or Developer.
• Experience building dashboards and semantic models in Microsoft Power BI.
• Knowledge of DAX, Power Query, and report optimization.
• Hands-on experience with ETL/ELT development in Azure Synapse Analytics and/or Databricks.
• Strong proficiency in SQL, Python, PySpark, and data transformation techniques.
• Experience with data orchestration tools such as Synapse Pipelines, ADF, or Databricks Workflows.
• Strong knowledge of data warehousing concepts and dimensional modeling.
• Familiarity with cloud storage (ADLS Gen2, Delta Lake, Parquet).
• Understanding of CI/CD, DevOps, and source control for analytics solutions.
• Experience working with large-scale enterprise data and integrating multiple source systems.
• Experience with lakehouse architecture and Delta tables.
• Knowledge of data governance and security practices.
• Experience supporting AI/ML or advanced analytics use cases.
• Microsoft Azure certifications (e.g., DP-203, PL-300).
• Experience in public sector or transportation data environments.