
Cloud data Engineer
1 week ago
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.
- 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.
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