Sr. Data Engineer

Job Title

Sr. Data Engineer

Chicago, IL

STAFFXPERT is seeking a highly skilled and motivated Sr. Data Engineer to join the Analytics Engineering team. This role will be responsible for designing, building, and maintaining scalable data pipelines and analytics solutions while contributing to the development of a semantic data layer, modern data products, and AI-driven solutions that support business growth and enhance customer experiences.

• Design, develop, and deploy scalable and robust data pipelines for seamless data integration and processing.
• Build and maintain enterprise-grade ETL/ELT frameworks, reusable libraries, and data processing solutions.
• Develop and optimize data models, semantic layers, and curated data products.
• Implement analytics engineering best practices, including coding standards, data governance, quality assurance, automation, and performance optimization.
• Participate in code reviews and contribute to continuous improvement of engineering standards and methodologies.
• Monitor, troubleshoot, and maintain data pipelines to ensure reliability, availability, and performance.
• Design and implement CI/CD pipelines to streamline deployment, testing, and maintenance processes.
• Collaborate with Data Scientists, Analysts, Product Managers, Engineers, and Business Stakeholders to translate business requirements into scalable technical solutions.
• Communicate complex technical concepts effectively to both technical and non-technical stakeholders.
• Support Advanced Analytics, Business Intelligence, and AI initiatives through high-quality data engineering solutions.

• 10+ years of professional experience in Data Engineering, Analytics Engineering, or related fields.
• Strong hands-on experience with:
  • SQL
  • Python
  • dbt
  • Snowflake
  • Apache Airflow
  • Git / Version Control Systems
• Proven experience designing and building scalable data pipelines and modern data architectures.
• Strong expertise in ETL/ELT development and data integration from multiple enterprise data sources.
• Deep understanding of data warehousing concepts and data modeling techniques.
• Experience with CI/CD tools and deployment workflows.
• Strong knowledge of data governance, data quality, and performance optimization.
• Excellent analytical, troubleshooting, and problem-solving skills.
• Ability to work effectively in a collaborative and fast-paced environment.
• Experience supporting Business Intelligence, Data Science, Advanced Analytics, or AI/ML initiatives.

• Minimum 10+ years of experience.
• Linked In profile must be verified using a work email.
• Strong recent experience with Snowflake, dbt, Python, SQL, and Airflow is required.