Data Engineer

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 complex problems down into their fundamental elements, we create modern digital solutions that drive efficiency, 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 and engagement, setting a higher standard for impactful work. Be a part of our team and shape a better future.

Position Summary

Element Solutions is looking for an analytical and critical thinking Data Engineer. The Data Engineer is responsible for designing, developing, implementing, and maintaining scalable data pipelines and data solutions that support customer and organizational needs. This role leverages Snowflake and Apache Airflow to build and manage data integration workflows, optimize data processing, and ensure data quality, reliability, and accessibility.

The Data Engineer works collaboratively with senior engineers, software developers, data analysts, and other project stakeholders to translate technical and business requirements into effective data solutions. This position requires hands-on experience with cloud-based data platforms, workflow orchestration, SQL development, automation, and data pipeline monitoring. The ideal candidate can independently manage routine engineering tasks, troubleshoot technical issues, and contribute to the continuous improvement of data infrastructure and engineering practices.

Key Responsibilities

Data Pipeline Development and Management

• Design, build, and maintain reliable, scalable ETL/ELT pipelines for ingesting, transforming, and delivering data.
• Develop Apache Airflow DAGs to orchestrate pipeline tasks, schedules, dependencies, and data-processing workflows.
• Integrate data from sources such as databases, APIs, and files, applying appropriate transformations and preserving data consistency.
• Develop SQL transformations and Snowflake data structures to support downstream data use.
• Build reusable pipeline components and automate recurring processes to improve maintainability and reduce manual effort.
• Support pipeline configuration and deployments across development, test, and production environments.

Snowflake Development and Optimization

• Develop and maintain Snowflake database objects, including schemas, tables, and views.
• Implement data loading and transformation processes using Snowflake capabilities and the organization’s approved integration tools.
• Optimize SQL queries and Snowflake workloads by evaluating query performance, warehouse sizing and utilization, and cost.
• Apply appropriate Snowflake data modeling and performance optimization techniques, including clustering when beneficial for the workload.
• Implement and maintain Snowflake roles and permissions in accordance with organizational and customer security requirements.

Workflow Orchestration and Automation

• Configure Airflow schedules, task dependencies, retries, timeouts, and failure handling to support reliable data workflows.
• Monitor workflow runs, investigate failures, and implement corrective actions to prevent recurring issues.
• Configure alerts and operational logging to support timely detection and troubleshooting of pipeline issues.
• Develop Python scripts and automation to support pipeline operations; use SQL where appropriate for data transformations.
• Maintain workflow and operational documentation, including dependencies, recovery steps, and troubleshooting guidance.

Data Quality, Testing, and Security

• Develop and maintain automated data validation checks and tests to assess accuracy, completeness, consistency, and integrity.
• Investigate and resolve data-quality issues, documenting their causes and corrective actions.
• Follow established data governance, privacy, security, and access-management requirements when handling data.
• Document data lineage and transformation logic to support traceability and maintainability.
• Follow established procedures for error handling and data recovery, and support compliance with applicable customer, organizational, and regulatory requirements.

Collaboration and Continuous Improvement

• Work with technical teams and stakeholders to clarify data requirements and deliver practical engineering solutions.
• Participate in code reviews, technical design discussions, and development planning.
• Contribute to shared engineering practices for version control, automated testing, and CI/CD.
• Identify and propose improvements to the reliability, scalability, maintainability, and cost efficiency of data solutions.
• Share knowledge with teammates and provide technical guidance when appropriate.
• Perform other related duties as assigned.

Minimum Requirements

• Bachelor's degree in Computer Science, Data Engineering, Information Systems, Software Engineering, or Associates degree plus two years' experience.
• At least 3 years of professional experience in data engineering, data integration, ETL/ELT development, or a related technical field.
• At least 3 years of hands-on experience with Snowflake and Apache Airflow in data engineering or data pipeline development.
• Strong proficiency in SQL, including query development, data transformation, and performance optimization.
• Experience developing, scheduling, monitoring, and troubleshooting data pipelines using Apache Airflow.
• Experience designing and maintaining data structures, transformations, and workflows in Snowflake.
• Proficiency in Python or a comparable scripting language for automation and data processing.
• Understanding of relational databases, data modeling, data integration patterns, and data quality practices.
• Experience with version control tools such as Git and collaborative software development practices.
• Strong analytical, troubleshooting, and problem-solving skills.
• Ability to work independently on assigned engineering tasks while collaborating effectively with technical teams and stakeholders.
• Must live in the Continental US.
• Be either a US citizen or Permanent Resident due to the work we do.
• Depending on agency requirements, you may need to possess or obtain a Public Trust designation or security clearance. Regardless of the specific requirement, all positions require the successful completion of a background check, background investigation, and the standard onboarding process.

Preferred Qualifications

• Experience supporting data engineering solutions in a government contracting, healthcare CMS (Center of Medicare & Medicaid) or in the health industry, or other regulated environment.
• Experience with cloud platforms such as AWS, Microsoft Azure, or Google Cloud Platform.
• Familiarity with cloud-based storage services and data ingestion tools.
• Experience implementing CI/CD pipelines and automated testing for data workflows.
• Knowledge of data governance, data lineage, metadata management, and role-based access controls.
• Experience working with REST APIs, JSON, and other structured or semi-structured data formats.
• Familiarity with containerization technologies such as Docker.
• 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.

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.

We believe in a world where solutions we build improve the lives of those who use them.