Data Engineer (Azure Synapse)

Datamatics Technologies•201 District, VA

1d•Remote

About The Position

We are looking for a Data Engineer to design, build, and manage scalable data pipelines and cloud-based data platforms on Microsoft Azure. The role will focus on enabling reliable data availability, supporting advanced analytics, and ensuring the scalability and performance of the Azure Data Lake and Synapse environment.

Requirements

3–6 years of experience in data engineering or cloud data platform development.
Strong hands-on experience with Azure Synapse Analytics
Azure Data Lake Storage (ADLS Gen2)
Azure Data Factory or Synapse Pipelines
Proficiency in SQL and Python/PySpark.
Experience with data warehousing concepts, dimensional modeling, and data transformation.
Understanding of data integration, pipeline orchestration, and performance tuning.

Nice To Haves

Experience supporting Power BI or enterprise BI solutions.
Exposure to CI/CD and DevOps for data pipelines.
Knowledge of data governance, security, and role-based access control (RBAC) in Azure.
Experience with real-time or streaming data is a plus.
Familiarity with enterprise data environments (ERP/SAP, CRM, etc.).

Responsibilities

Design and develop ETL/ELT pipelines to ingest data from multiple source systems into Azure Data Lake (ADLS).
Build and manage data processing workflows using Azure Synapse Analytics.
Develop data transformation logic using PySpark, SQL, or Azure Synapse pipelines.
Integrate data from enterprise systems (SAP, APIs, databases, flat files, etc.) into the centralized data platform.
Optimize data models and queries for performance, scalability, and cost efficiency.
Ensure data quality, validation, monitoring, and error handling across pipelines.
Support Power BI datasets and reporting requirements by preparing curated data layers.
Implement data governance, security, and access controls in line with organizational policies.
Monitor pipeline performance and troubleshoot data issues proactively.
Collaborate with analytics, business, and IT teams to understand data requirements and support change requests.