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.
Key Responsibilities
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.
Required Skills & Qualifications
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.
Mandatory Screening Criteria
Minimum 10 years of experience.
LinkedIn profile must be verified using a work email.
Strong recent experience with Snowflake dbt Python SQL and Airflow is required.
Job Title: Sr. Data Engineer Location: Chicago IL About the Role 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 whil...
Job Title: Sr. Data Engineer
Location: Chicago IL
About the Role
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.
Key Responsibilities
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.
Required Skills & Qualifications
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.
Mandatory Screening Criteria
Minimum 10 years of experience.
LinkedIn profile must be verified using a work email.
Strong recent experience with Snowflake dbt Python SQL and Airflow is required.