Data Engineer

Element Solutions is hiring a Data Engineer to design, develop, implement, and maintain scalable data pipelines and solutions that meet customer and organizational needs. The role uses Snowflake and Apache Airflow to integrate and process data, ensure data quality and reliability, and improve data infrastructure in collaboration with technical teams and stakeholders.

Responsibilities:

• 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
• 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
• 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
• 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
• 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

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
• Be either a US citizen or Permanent Resident due to the work we do
• 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