Senior Engineer, Quality Assurance 1 1

PRIMARY RESPONSIBILITIES / KEY RESULT AREAS Utilize a rigorous design methodology that consistently yields the right level of technical design documentation and develop technical solutions that conform both to customer requirements and information development standards. Building value-creating and innovative data solutions. Use a vast amount of programming tools to design new data solutions to ingest and integrate data into Unified Data Platform. Understand various requirement gathering and specification methodologies and can recommend one appropriate to a project. Designing, Implementing, and supporting a platform that can provide access to large datasets. Work as equals with Data Engineers, Quality Engineers, BI Developers and Business Analysts to establish optimal design/development/delivery which properly serves technical teams and our user community. Identify risks, tradeoffs, and investment decisions to facilitate best practices. COMPETENCIES Strong problem-solving skills with acute attention to detail and ability to meet tight deadlines and project plans. Design and develop complex, large scale data structures and pipelines to organize, collect and standardize data that generate insights and address analytical/reporting needs. Design standards and best practices into new data engineering solutions. Proactively identify performance and data quality problems and drive to remediate them. Manage code versions and deployment process in source control and coordinate changes across team. Partner with Product Management and Operation teams to proactively identify monitoring gaps and improving upstream data collection and advocating for data driven thinking. Assist in running code reviews, guide team to follow standards, supporting team members in brainstorming and challenging designs. Solve and help other team members complex data issues around data integration of structured and unstructured sets other data processing incidents. QUALIFICATIONS EXPERIENCE Bachelor s degree in Computer Science, Computer Engineering, Information Systems, or related technology. Minimum of 6 years of relevant data processing experience; 3+ years utilizing cloud-based services and data streaming. Experience with large scale data lake and data warehouse implementations in cloud environments. Expertise building data lakes and data warehouses in Snowflake using DBT, Phyton, Snowpark, Snowpipe and Snowflake SQL. Experience with Continuous Integration Continuous Delivery (Jenkins) Experience in data analysis and writing and developing complex queries using SQL. Strong communication skills including technical documentation, development and delivery of demonstrations and presentations and the ability to listen and communicate effectively with functional leaders.