Job Summary
We are seeking two experienced Senior Data Engineers to support a federal project focused on building secure, scalable, and analysis-ready data solutions. The ideal candidate will have strong hands-on experience with Python, SQL, Azure Data Factory, Databricks, ETL/ELT pipelines, data modeling, and cloud-based data platforms.
This role will support the design, development, and optimization of enterprise data pipelines, data warehouses, and lakehouse environments. The Senior Data Engineer will work closely with data scientists, analysts, cloud engineers, and technical stakeholders to ensure data systems are reliable, secure, high-performing, and ready for advanced analytics and reporting.
Key Responsibilities
Design, develop, and maintain enterprise-grade ETL/ELT pipelines using Python and SQL.
Build and optimize scalable data pipelines using Azure Data Factory, Databricks, PySpark, and related cloud data tools.
Develop processes to ingest, clean, validate, and transform large-scale datasets from APIs, relational databases, flat files, and unstructured sources.
Design and maintain data models, data warehouses, data lakes, and lakehouse environments.
Implement data quality checks, metadata management, validation rules, and governance controls.
Collaborate with cloud engineering teams to deploy and manage data solutions in Microsoft Azure.
Monitor, troubleshoot, and optimize pipeline performance using logging, alerting, and CI/CD best practices.
Support data security, access control, compliance, and governance requirements for enterprise and federal data environments.
Document data architecture, pipeline logic, operational procedures, and technical designs.
Work with data scientists, analysts, and business stakeholders to deliver reliable data solutions that support decision-making.
Required Qualifications
8+ years of experience in data engineering, software engineering, database architecture, or related technical roles.
6+ years of hands-on experience with Python and SQL.
Experience designing and building scalable ETL/ELT pipelines.
2+ years of experience with cloud data ecosystems, preferably Microsoft Azure.
Hands-on experience with Azure Data Factory.
Hands-on experience with Databricks, PySpark, Spark SQL, or similar modern data processing frameworks.
Experience working with data warehouses, data lakes, or lakehouse architectures.
Experience ingesting and transforming data from APIs, flat files, relational databases, and other enterprise systems.
Strong knowledge of relational databases, NoSQL databases, data modeling, and schema design.
Experience with data quality, data validation, metadata, governance, security, and compliance practices.
Experience with CI/CD, Git, logging, monitoring, and troubleshooting production data pipelines.
Bachelor’s degree in Computer Science, Engineering, Information Systems, Data Science, or a related quantitative field.
Preferred Qualifications
Experience supporting federal government, healthcare, public health, or CDC-related data environments.
Experience with Azure Data Lake Storage, Azure SQL, Azure Synapse, Microsoft Fabric, Delta Lake, or Snowflake.
Experience working with data scientists and analysts to design analytics-ready datasets.
Knowledge of enterprise data access controls, security frameworks, and compliance requirements.
Experience with Agile/Scrum development environments.
Azure Data Engineer Associate certification or related cloud/data certification.
Public Trust or ability to obtain a federal clearance
Pay: $70.00 - $85.00 per hour
Work Location: Remote
