Senior Data Engineer
Washington D.C.On-siteFull-time
AI Summary
Senior Data Engineer builds and optimizes data pipelines in Databricks, SQL, and ETL processes to support enterprise decision-making.
About this role
Who we are:
Makpar is a comprehensive professional and technical solutions provider for the Federal government. We combine functional and technical expertise in cloud engineering, data management, cybersecurity and emerging technologies to deliver mission success. We build the right IT solution for government clients by partnering with them to understand their WHAT, WHY, and HOW. Using our signature consulting methodology that we call “The Makpar Way,” we help agencies navigate the ongoing changes in the Federal technology landscape. We succeed where others fail because of our connected and engaged workforce are dedicated to delivering success for our clients and the American people.
Our Mission: We solve complex problems for the Federal government to accelerate access to citizen services.
When it comes to excellence, we deliver. Learn more about our employer brand at makpar.com/careers.
Makpar has an exciting opportunity for a Senior Data Engineer. This role requires expertise in Databricks, SQL, and ETL pipelines, with strong experience building scalable data frameworks to support enterprise decision-making.
Key Responsibilities:
- Build, test, and orchestrate data pipelines in Databricks.
- Design and optimize data structures, schemas, and ETL processes.
- Translate business use cases into SQL queries, reports, and dashboards.
- Manage database objects in development environments without impacting production.
- Automate workflows using Databricks Workflows or the Jobs API.
- Integrate code into GitHub/GitLab and support CI/CD practices.
- Diagnose data gaps/quality issues and design test cases for validation.
- Collaborate with developers and analysts to synchronize code and ensure reliability.
Qualifications
- Active Secret clearance (mandatory requirement).
- Bachelor’s or Master’s degree in Computer Science, Data Engineering, or related field.
- 7+ years of professional experience in data engineering.
- Expert-level proficiency in Databricks, Apache Spark, and SQL.
- Experience with Kafka, Airflow, or AWS Glue for ETL.
- Proficiency in CI/CD pipelines and GitHub/GitLab version control.
- Knowledge of cloud platforms (AWS, Azure, GCP).
- Excellent problem-solving, debugging, and collaboration skills.
Clearance Requirement
- Active Secret clearance (mandatory requirement).
Skills
AirflowApache SparkAWSAWS GlueAzureCI/CDData ArchitecturesDatabricksDatabricks WorkflowsData ModelingData QualityDevOpsETL PipelinesGCPGitHubGitLabJobs APIKafkaSQLTesting Pipelines
