Sr. 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 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: Element Solutions is looking for a driven and experienced Data Engineer to support a government contract working hybrid, with additional on-site presence as required by the client.  The Senior  Data Engineer is responsible for designing, building, and maintaining scalable data infrastructure that supports enterprise data processing and analytics initiatives. This role develops and manages data pipelines, ETL processes, and storage solutions that enable efficient collection, transformation, and delivery of data from multiple sources. The Senior Data Engineer collaborates closely with data scientists, analysts, and technical teams to ensure data platforms are reliable, performant, and optimized for advanced analytics and business intelligence. 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. This position is hybrid in Washington, DC and will require additional on-site work as requested by the client.  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. Key Responsibilities Design, construct, and maintain the infrastructure and architecture required for large-scale data processing systems. Develop and implement data pipelines, ETL processes, and data integration workflows to collect, transform, and deliver data from diverse data sources. Build and maintain scalable data storage solutions, including data lakes, data warehouses, and cloud-based data platforms. Collaborate with data scientists, analysts, and application developers to ensure data accessibility and usability for analytics and reporting. Optimize data systems for performance, scalability, and reliability. Implement data quality checks, validation processes, and monitoring to ensure data integrity. Support the development and maintenance of data models and data architectures that align with business and analytical requirements. Troubleshoot and resolve issues related to data pipelines, infrastructure, and system performance. Maintain documentation for data architecture, workflows, and technical processes. Stay current with industry trends, emerging technologies, and best practices in data engineering and data architecture. Minimal Requirements Bachelor’s degree in Computer Science, Data Engineering, Information Systems, or related field. Minimum 8 years of professional experience in data engineering, data integration, or a related technical field, including 3+ years in a leadership role. Ability to document data flows, data dependencies, and technical processes in support of business process analysis. Experience supporting data-intensive, analytical, research, financial, or regulatory environments. Demonstrated experience designing, developing data pipelines, data transformations, and data workflows. Strong experience developing ETL/ELT pipelines and large-scale data processing solutions. Familiarity with data governance, data quality, metadata, and access control considerations. Proficiency with SQL and programming languages such as Python, Java, or Scala. Experience working with relational and/or non-relational databases and data storage technologies. Strong understanding of data modeling, data warehousing, and data integration concepts. Ability to support modernization or migration efforts from legacy data environments. Strong analytical and problem-solving skills. Excellent communication and collaboration abilities. Ability to work effectively in agile, hybrid, or iterative delivery environments, including collaboration with cross-functional teams and incremental solution delivery. US Citizenship required. Must reside in the Continental US; and be within driving distance to Washington, DC. Depending on the government agency, specific requirements may include public trust background check or security clearance. Preferred Qualifications Experience supporting data pipelines used for modeling, forecasting, or analytical workloads. Demonstrated experience in analyzing interdependencies across data pipelines, repositories, analytical models, and workflows. Familiar with cloud-based data platforms and services (AWS preferred) and modern data engineering tools. Familiar with programming languages used for data analytics (e.g., R, SAS, Stata, etc.) Familiar with data pipeline and orchestration tools (e.g., Databricks, Apache Airflow, AWS, Glue, Informatica, etc.) Experience working in environments with federated ownership models and complex governance structures. 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 .

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      "text": "Key Responsibilities ",
      "content": "<div>\n\n<li>Design, construct, and maintain the infrastructure and architecture required for large-scale data processing systems.</li>\n<li>Develop and implement data pipelines, ETL processes, and data integration workflows to collect, transform, and deliver data from diverse data sources.</li>\n<li>Build and maintain scalable data storage solutions, including data lakes, data warehouses, and cloud-based data platforms.</li>\n<li>Collaborate with data scientists, analysts, and application developers to ensure data accessibility and usability for analytics and reporting.</li>\n<li>Optimize data systems for performance, scalability, and reliability.</li>\n<li>Implement data quality checks, validation processes, and monitoring to ensure data integrity.</li>\n<li>Support the development and maintenance of data models and data architectures that align with business and analytical requirements.</li>\n<li>Troubleshoot and resolve issues related to data pipelines, infrastructure, and system performance.</li>\n<li>Maintain documentation for data architecture, workflows, and technical processes.</li>\n<li>Stay current with industry trends, emerging technologies, and best practices in data engineering and data architecture.&nbsp;</li>\n\n</div>"
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