Saxon Global
Cloud data Engineer
Saxon Global, Madison, Wisconsin, us, 53774
Role: Certified Cloud Engineer
End Client: State of WI.
Contract Length: 9+months
Work Type: LOCAL CANDIDATES TO WI. CAN WORK 100% REMOTE
Location: Madison, WI.
Rate C2C: 100/hr
Work Auth - All Except H1B
***Please send proof of legal location. I will only be accepting candidates who are currently RESIDING IN WI***
Job Summary:
Collaborate with data engineering and development teams to design, develop, test, and maintain robust and scalable ELT/ETL pipelines using SQL scripts, Redshift stored procedures, and other AWS tools and services.Collaborate with our engineering and data teams to understand business requirements and data integration needs, translate them into effective data solutions, that yield top-quality outcomes.Architect, implement, and manage end-to-end data pipelines, ensuring data accuracy, reliability, data quality, performance, and timeliness.Employ AWS DMS and other services for efficient data ingestion from on-premises databases into Redshift.Design and implement ETL processes, encompassing Changed Data Capture (CDC) and Slow Changing Dimension (SCD) logics, to seamlessly integrating data from diverse source systems.Provide expertise in Redshift database optimization, performance tuning, and query optimization.Design and implement efficient orchestration workflows using Airflow, ensuring seamless coordination of complex ETL processes.Integrate Redshift with other AWS services, such as AWS DMS, AWS Glue, AWS Lambda, Amazon S3, Airflow, and more, to build end-to-end data pipelines.Perform data profiling and analysis to troubleshoot data-related challenges / issues and build solutions to address those concerns.Proactively identify opportunities to automate tasks and develop reusable frameworks.Work closely with version control team to maintain a well-organized and documented repository of codes, scripts, and configurations using Git.Provide technical guidance and mentorship to fellow developers, sharing insights into best practices, tips, and techniques for optimizing Redshift-based data solutions.REQUIRED SKILLS:
12+ years of experience with AWS stack including:
Glue, Spark, Python, and Redshift.
10+ years working with and personally implementing solutions involving the following concepts:
CDC (Change Data Capture), SCD (Slowly Changing Dimensions), and surrogate keys.
Proficient in SQL and Redshift for data manipulation.Hands-on experience with AWS services like DMS, S3, Glue, Redshift, and Airflow.Strong ETL knowledge and data modeling skills.Skilled in complex ETL scenarios and data integration.Expertise in AWS DMS for on-prem to cloud data migration.Proficient in Python for Airflow DAGs and operators.Oracle to Redshift script conversion experience.Familiar with Git for version control.Adept at identifying and optimizing Redshift queries.Strong problem-solving skills with data accuracy focus.Collaborative, agile team player with technical communication skills.Proven track record of on-time, high-quality data solutions.Experience in large-scale data environments.Extensive Redshift and AWS experience for scalable solutions.AWS data engineering or database certifications are a plus.
End Client: State of WI.
Contract Length: 9+months
Work Type: LOCAL CANDIDATES TO WI. CAN WORK 100% REMOTE
Location: Madison, WI.
Rate C2C: 100/hr
Work Auth - All Except H1B
***Please send proof of legal location. I will only be accepting candidates who are currently RESIDING IN WI***
Job Summary:
Collaborate with data engineering and development teams to design, develop, test, and maintain robust and scalable ELT/ETL pipelines using SQL scripts, Redshift stored procedures, and other AWS tools and services.Collaborate with our engineering and data teams to understand business requirements and data integration needs, translate them into effective data solutions, that yield top-quality outcomes.Architect, implement, and manage end-to-end data pipelines, ensuring data accuracy, reliability, data quality, performance, and timeliness.Employ AWS DMS and other services for efficient data ingestion from on-premises databases into Redshift.Design and implement ETL processes, encompassing Changed Data Capture (CDC) and Slow Changing Dimension (SCD) logics, to seamlessly integrating data from diverse source systems.Provide expertise in Redshift database optimization, performance tuning, and query optimization.Design and implement efficient orchestration workflows using Airflow, ensuring seamless coordination of complex ETL processes.Integrate Redshift with other AWS services, such as AWS DMS, AWS Glue, AWS Lambda, Amazon S3, Airflow, and more, to build end-to-end data pipelines.Perform data profiling and analysis to troubleshoot data-related challenges / issues and build solutions to address those concerns.Proactively identify opportunities to automate tasks and develop reusable frameworks.Work closely with version control team to maintain a well-organized and documented repository of codes, scripts, and configurations using Git.Provide technical guidance and mentorship to fellow developers, sharing insights into best practices, tips, and techniques for optimizing Redshift-based data solutions.REQUIRED SKILLS:
12+ years of experience with AWS stack including:
Glue, Spark, Python, and Redshift.
10+ years working with and personally implementing solutions involving the following concepts:
CDC (Change Data Capture), SCD (Slowly Changing Dimensions), and surrogate keys.
Proficient in SQL and Redshift for data manipulation.Hands-on experience with AWS services like DMS, S3, Glue, Redshift, and Airflow.Strong ETL knowledge and data modeling skills.Skilled in complex ETL scenarios and data integration.Expertise in AWS DMS for on-prem to cloud data migration.Proficient in Python for Airflow DAGs and operators.Oracle to Redshift script conversion experience.Familiar with Git for version control.Adept at identifying and optimizing Redshift queries.Strong problem-solving skills with data accuracy focus.Collaborative, agile team player with technical communication skills.Proven track record of on-time, high-quality data solutions.Experience in large-scale data environments.Extensive Redshift and AWS experience for scalable solutions.AWS data engineering or database certifications are a plus.