The Data Engineer will build and maintain scalable data pipelines, ensure data quality, and collaborate with teams to meet data requirements for federal government projects.
Who is Element?
We serve as a partner at the intersection of innovation and our clients' needs, efficiently crafting meaningful user experiences for government and commercial customers. By breaking down complex problems to their fundamental elements, we create modern digital solutions that drive efficiencies, maximize taxpayer dollars, and deliver essential outcomes that serve the people.
Why Work at Element?
Make an impact that resonates-join our vibrant team and discover how you can improve lives through digital transformation. Our talented professionals bring unparalleled energy engagement, setting a higher standard for impactful work. Come be a part of our team and shape a better future.
Position Summary:
We are seeking a driven Data Engineer to support a federal government contract focused on designing, building, and maintaining scalable data pipelines for enterprise-level data integration. The Data Engineer will be responsible for ensuring reliable, high-quality data flow across multiple systems while enabling analytics, reporting, and downstream application use cases.
This role requires strong experience in distributed data systems, real-time and batch processing, and working in secure, regulated government environments.
Key Responsibilities
- Build and maintain high-volume, scalable data pipelines using Apache Kafka and Apache Spark, supporting both real-time and batch data processing needs.
- Design, develop, and optimize data ingestion, transformation, and integration workflows across enterprise systems.
- Ensure data quality, consistency, and integrity across four (4) disparate data sources, implementing validation, cleansing, and reconciliation processes.
- Develop and maintain SQL-based data solutions, including complex queries, stored procedures, performance tuning, and data modeling.
- Collaborate with data analysts, product owners, and application teams to define data requirements and ensure alignment with business needs.
- Implement monitoring, logging, and alerting mechanisms to ensure reliability and observability of data pipelines.
- Support data architecture design and contribute to best practices for scalable and secure data engineering solutions.
- Ensure compliance with federal data governance, security, and privacy requirements.
- Participate in Agile ceremonies and support iterative development and delivery of data capabilities.
- Troubleshoot and resolve data pipeline issues, ensuring minimal disruption to downstream systems and reporting.
Minimum Requirements
- Bachelor’s degree in Computer Science, Information Systems, Engineering, Data Science, or related field (or equivalent experience).
- 3+ years of experience in data engineering, data integration, or related technical roles.
- Strong hands-on experience with Apache Kafka for streaming data pipelines.
- Strong experience with Apache Spark for large-scale data processing (batch and/or streaming).
- Advanced SQL development experience, including complex queries, performance tuning, and data transformation logic.
- Experience integrating and managing data across multiple heterogeneous data sources.
- Experience working in the federal government or other highly regulated environments with security and compliance requirements.
- Strong understanding of data quality management, data validation, and data governance practices.
- Strong problem-solving and analytical thinking abilities.
- Excellent communication skills, with the ability to explain technical concepts to non-technical stakeholders.
- Strong attention to detail, especially in ensuring data accuracy and consistency.
- Ability to work independently in a fast-paced, mission-driven environment.
- Strong collaboration skills across cross-functional technical and business teams.
- US Citizenship or Permanent Residency required.
- Must reside in the Continental US.
- Depending on the government agency, specific requirements may include public trust background check or security clearance.
Preferred Qualifications
- AWS Data Engineer certification.
- Experience with cloud platforms such as AWS, Azure, or GCP (especially data services like S3, Glue, Databricks, or BigQuery).
- Familiarity with data orchestration tools (e.g., Airflow, NiFi, or similar).
- Experience supporting healthcare, insurance, or CMS-related data environments.
- Knowledge of data modeling techniques (dimensional modeling, star/snowflake schemas).
- Experience with DevOps practices, CI/CD pipelines, and infrastructure-as-code for data systems.
- Familiarity with real-time analytics and event-driven architectures.
- Qualified individuals living in HUBZone-certified areas are strongly encouraged to apply. To find out if you live in a HUBZone go to: https://maps.certify.sba.gov/hubzone/map#center=44.722800,-103.249700&zoom=4.
Our People
We invest in the lives of our employees, both in and out of the workplace, by providing competitive pay and benefits packages. Benefits offered may include health care, dental, vision, life insurance; 401(k); paid time off including PTO, holidays, and any other paid leave required by law.
Location
Be in your Element. We are a remote first company based out of Washington, DC. As a HUBZone-certified business we are committed to supporting local economic development.
Element is an equal opportunity employer All qualified applicants will receive consideration for employment without regard to age, ancestry, race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or veteran status, marital status, protected veteran status, or any other legally protected class.
We believe in a world where solutions we build improve the lives of those who use them.
Similar Jobs
Artificial Intelligence • Big Data • Healthtech • Information Technology • Machine Learning • Software • Analytics
The Principal Data Engineer will design, implement, and lead data solutions, working closely with teams using technologies like Azure Databricks and Kafka, mentoring junior engineers, and improving CI/CD and DataOps practices.
Top Skills:
Amazon)Apache KafkaAzure DatabricksCloud Computing (AzureGitGithub ActionsGooglePythonSnowflakeSQL
Cloud • Computer Vision • Information Technology • Sales • Security • Cybersecurity
The Data Engineer will architect and develop robust data frameworks for data platforms, focusing on data transformations and automated workflows. Responsibilities include collaborating with stakeholders, ensuring data quality, and maintaining high engineering standards.
Top Skills:
AirflowDbtGitGitlab Ci/CdJenkinsPythonSnowflake
Healthtech • Software
As a Data Engineer, you will transform raw healthcare data into quality intelligence products, lead product development, and mentor junior engineers while collaborating cross-functionally.
Top Skills:
BigQueryDagsterDbtGoogle Cloud StoragePython
What you need to know about the NYC Tech Scene
As the undisputed financial capital of the world, New York City is an epicenter of startup funding activity. The city has a thriving fintech scene and is a major player in verticals ranging from AI to biotech, cybersecurity and digital media. It also has universities like NYU, Columbia and Cornell Tech attracting students and researchers from across the globe, providing the ecosystem with a constant influx of world-class talent. And its East Coast location and three international airports make it a perfect spot for European companies establishing a foothold in the United States.
Key Facts About NYC Tech
- Number of Tech Workers: 549,200; 6% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Capgemini, Bloomberg, IBM, Spotify
- Key Industries: Artificial intelligence, Fintech
- Funding Landscape: $25.5 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Greycroft, Thrive Capital, Union Square Ventures, FirstMark Capital, Tiger Global Management, Tribeca Venture Partners, Insight Partners, Two Sigma Ventures
- Research Centers and Universities: Columbia University, New York University, Fordham University, CUNY, AI Now Institute, Flatiron Institute, C.N. Yang Institute for Theoretical Physics, NASA Space Radiation Laboratory
