EA DT Engineer
About The Position
Design, develop, and deliver large-scale data systems, data processing, and data transformation pipelines. Collaborate with stakeholders to understand business needs and work with business teams to deliver enterprise-grade datasets that are reliable, flexible, scalable, and low-cost to own. Develop optimized, scalable batch integration solutions, including traditional data warehouse workloads and scheduled nightly large extracts. Extract data from various sources, transform it into a usable format, and load it into Azure Data Lake using ADF pipelines, Databricks, PySpark, and SQL. Design and build data models, including star and snowflake schemas, and work with common analytical models such as Kimball. Build physical data models aligned with best practices and requirements. Plan, review, and perform database-change implementations for integration and data warehouse work. Work with the BI team and product owner to build required tables and transform data for loading into Snowflake and Dremio. Perform data management tasks and recommend improvements to data reliability, efficiency, and quality. The role is based at ABC Supply’s Beloit, Wisconsin office and requires onsite work five days per week. The stated salary range is $123,600–$130,000 per year.
Requirements
- A master’s degree in Computer Science, IT/IS, or a related field and two years of work experience in the job offered or a related occupation; alternatively, a bachelor’s degree in Computer Science, IT/IS, or a related field and five years of such experience.
- Demonstrated experience with enterprise integration patterns (EIP), data warehouse modeling, ETL processes, and database management.
- Demonstrated experience in development and data warehouse requirements gathering, analysis, and design.
- Demonstrated experience with cloud-native modern data engineering projects.
- Demonstrated experience designing, building, and deploying scalable data pipelines.
- Demonstrated experience with Python, PySpark, and Spark SQL.
- Demonstrated experience with analytical data models such as Kimball.
Responsibilities
- Design, develop, and deliver large-scale data systems, data processing, and data transformation pipelines.
- Collaborate with stakeholders to understand business needs and deliver reliable, flexible, scalable, and low-cost enterprise datasets.
- Develop optimized, scalable batch integration solutions, including traditional data warehouse workloads and scheduled nightly large extracts.
- Extract data from various sources, transform it, and load it into Azure Data Lake using ADF pipelines, Databricks, PySpark, and SQL.
- Design and build star-schema, snowflake-schema, and physical data models aligned with best practices and requirements.
- Plan, review, and implement database changes for integration and data warehouse work.
- Work with the BI team and product owner to build required tables and transform data for loading into Snowflake and Dremio.
- Perform data management tasks.
- Recommend ways to improve data reliability, efficiency, and quality.
Benefits
- Health coverage, eligible after 60 days, with low out-of-pocket costs
- Dental coverage, eligible after 60 days, with low out-of-pocket costs
- Vision coverage, eligible after 60 days, with low out-of-pocket costs
- 401(k) with generous company match, eligible after 60 days and immediately vested
- Employer-paid employee assistance program
- Employer-paid short-term and long-term disability
- Employer-paid life insurance
- Flex spending
- Paid vacation
- Paid sick days
- Paid holidays
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
