This job offer is no longer available
About
Location: Leawood, KS
Job Type: Contract
Job Description
We are seeking a Senior Data Engineer with strong experience in building and maintaining modern data platforms, and a solid background in data quality, validation, and automation. This role is ideal for a hands-on data engineer who has worked closely with QE or testing teams and has personally implemented data testing frameworks, profiling, and reconciliation for large-scale data pipelines.
The candidate will play a key role in designing, developing, and validating Snowflake-based data platforms and ETL/ELT pipelines, ensuring data accuracy, reliability, performance, and governance across the data ecosystem.
Key Responsibilities Design, develop, and optimize ETL/ELT data pipelines for large-scale data platforms. Build and maintain Snowflake and SQL Server-based data warehouses. Perform advanced SQL-based data profiling, reconciliation, and validation to ensure data accuracy and integrity. Implement data quality checks, automation frameworks, and shift-left testing strategies within the data pipeline. Develop Python-based automation for data validation, testing, and monitoring. Integrate data quality and validation processes into CI/CD pipelines. Leverage tools such as Soda and Coalesce to enforce data quality, observability, and governance. Collaborate closely with Data Engineers, Architects, Analytics teams, and QE members to define best practices. Identify, analyze, and resolve complex data issues, performance bottlenecks, and pipeline failures. Support Agile delivery by participating in sprint planning, code reviews, and continuous improvement initiatives. Mentor junior engineers and promote strong data engineering and quality engineering practices. Required Skills & Experience
10-15 years of experience in Data Engineering, with exposure to data quality or data testing. Strong hands-on experience with Snowflake and SQL Server. Deep knowledge of Data Warehousing concepts, dimensional modeling, and data architecture. Extensive experience with ETL/ELT pipelines and large-scale data processing. Expert-level SQL for data profiling, validation, reconciliation, and performance tuning. Strong Python skills for automation, scripting, and data validation. Experience implementing data quality frameworks and automated data testing. Hands-on experience with Soda, Coalesce, or similar modern data stack tools. Solid understanding of QE processes, test strategies, and shift-left testing concepts. Experience working in Agile/Scrum environments. Strong knowledge of CI/CD pipelines and integrating data workflows into automated deployments. Excellent analytical, problem-solving, and communication skills.
Languages
- English
Notice for Users
This job was posted by one of our partners. You can view the original job source here.