Teams at i4DM

Designs and automates data validation, profiling, testing, monitoring, and quality frameworks for multi-source cloud data. The role uses Azure Synapse, Databricks, SQL, Python, Scala, Collibra, and Profisee to detect anomalies, enforce governance, and improve data reliability. Responsibilities include developing automated test plans, analyzing structured and unstructured datasets, supporting Azure data engineering workflows, and collaborating with engineers, analysts, data scientists, and product teams. A Public Trust or Suitability/Fitness determination may be required.

Designs and maintains scalable Azure data pipelines and ETL/ELT solutions across data lakes, warehouses, lakehouses, streaming platforms, and enterprise sources. Builds integrations using Azure Data Factory, Synapse, Databricks, Spark, Kafka, and related services; applies security, governance, monitoring, and performance optimization practices. Develops Power BI dashboards, reports, data models, and visualizations, while supporting analytics and AI/ML use cases. Collaborates in Agile teams and automates deployments through DevOps and CI/CD practices.

Designs, maintains, and optimizes SQL Server databases, ETL/ELT workflows, and enterprise data pipelines supporting a federal multi-cloud analytics platform. Integrates structured and unstructured data using Azure, Databricks, Starburst, and data lakes; troubleshoots failures, tunes performance, applies data-quality and governance controls, and supports analytics, reporting, and machine-learning use cases. Translates business requirements into technical solutions and documents data products, pipelines, and operational procedures.