Data Engineer
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Role details
Tech stack
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Job description
- Build, test, and maintain data pipelines using Python.
- Design and optimize data structures, schemas, and ETL processes.
- Develop SQL queries, reports, and dashboards to support business needs.
- Manage database objects across development and testing environments.
- Automate workflows using Databricks Workflows or Jobs API.
- Integrate code into GitHub/GitLab and support CI/CD processes.
- Troubleshoot data quality issues and perform data validation.
- Collaborate with developers, analysts, and stakeholders to deliver reliable data solutions.
Requirements
- Active Secret clearance (mandatory requirement).
- Local Residency in Maryland, Virginia or Washington, DC.
- Bachelor’s degree in computer science, Data Engineering, Information Systems, or a related field.
- 3-5 years of professional experience in data engineering.
- Experience with Databricks, Apache Spark, and SQL.
- Proficiency in Python and SQL.
- Experience with ETL tools such as Airflow, Kafka, or AWS Glue.
- Familiarity with GitHub/GitLab and CI/CD pipelines.
- Experience working with cloud platforms such as AWS, Azure, or GCP.
- Strong analytical, troubleshooting, and problem-solving skills.
- Excellent communication and collaboration skills.
Clearance Requirement:
- Active Secret clearance (mandatory requirement)., Amazon Web Services (AWS), Analysis Skills, Apache Spark, Application Programming Interface (API), Artificial Intelligence (AI), Automation, Best Practices, Business Support, Cloud Computing, Communication Skills, Computer Science, Consulting, Continuous Deployment/Delivery, Continuous Integration, Data Management, Data Quality, Data Structures, Database Administration, Database Extract Transform and Load (ETL), Database Programming, Emerging Technology, Federal Government, GCP (Good Clinical Practices), GitHub, Government, Identify Issues, Information Technology & Information Systems, Information/Data Security (InfoSec), Internet Security, Microsoft Windows Azure, Problem Solving Skills, Python Programming/Scripting Language, Reporting Dashboards, SQL (Structured Query Language), Scalable System Development, Secret Clearance, Software Engineering, Team Player, Technical Delivery, Test Plan/Schedule, Testing
Benefits & conditions
At Makpar Corporation we understand that we all need to balance work and life - that is why we have a great benefits package, excellent training and career development opportunities, flexible work schedules along with a generous compensation package. At Makpar, we believe in keeping our employees happy, healthy and engaged. We pride ourselves in providing outstanding benefits, creating environments where employees are encouraged to be themselves, collaborate, and be inquisitive in order to achieve goals.
Start your career today and be a part of something meaningful!
Makpar is an Equal Opportunity Employer.
About the company
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 an experienced Data Engineer to support a federal client in advancing enterprise-scale analytics and data-driven decision-making. The ideal candidate will design, build, and optimize cloud-based data pipelines using Python, SQL, and modern ETL frameworks while collaborating with analysts and developers to deliver scalable, reliable, and secure data solutions through CI/CD and automation best practices.
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