Develop data ingestion frameworks to extract data from enterprise applications, APIs, flat files, databases, and legacy systems. Design and implement end-to-end ETL/ELT pipelines for structured and unstructured data from multiple source systems.
Numbers & Facts
Location
Columbia, MD
Description
Position: Data Engineer/Analytics Developer (End-to-End ETL & BI) Work Location: 707 N. Calvert St, Baltimore, Maryland. This position follows a hybrid work schedule (work remotely up to 3 days per week). Interview Mode: In person
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.