Sr. Associate Data Engineer (PySpark, Python & ETL)
About The Position
Rx Savings Solutions, part of McKesson's CoverMyMeds organization, offers an innovative, patented software system that educates and empowers consumers to make the best healthcare choices at the lowest cost. Founded and operated by a team of pharmacists and software engineers, we support a collaborative, cost-saving solution for purchasing prescription drugs. We currently have an opportunity for a Sr Associate Data Engineer to join our growing Business Operations data engineering team! This is a junior-level position on our team (ideally looking for 2-4 years of Data Engineering / ETL experience). This assists in planning, designing, troubleshooting, and documenting technical requirements for data flows between disparate operational systems and our data warehouse. Our ideal candidate has hands-on experience building and supporting data pipelines using PySpark, SQL, and Python in a cloud-based data environment. Experience developing ETL processes, troubleshooting production data pipelines, and working with cloud technologies such as AWS, Databricks, Azure, or similar platforms is highly preferred. We are looking for engineers who can clearly articulate their contributions to designing, building, supporting, and optimizing data solutions in production environments.
Requirements
- Bachelor's degree in Computer Science or related technical degree, or equivalent experience, and 2+ years of experience relative to the above responsibilities
- 2+ years of experience building and supporting data pipelines using PySpark in a cloud-based data platform environment
- 2+ years of hands-on experience developing data transformation logic using PySpark and SQL
- 2+ years of experience Databricks or similar cloud-based data platforms
- 2+ years of hands-on Python development experience supporting ETL processes, automation, data transformation, or data quality initiatives
- Experience troubleshooting, supporting, and resolving issues within production ETL and data pipeline environments
- Knowledge of Structured and Unstructured data
- Possess understanding of BI concepts and be familiar with relational or multi-dimensional modeling concepts
- Understanding of RDBMS best practices and performance tuning techniques
- Experience with cloud technologies such as AWS services such as S3, CloudWatch, EC2, and passion for a role working in a cloud data warehouse.
- Experience with version control systems like Git
Nice To Haves
- Experience with Databricks
- Experience with AWS cloud services such as S3, CloudWatch, EC2, Glue, or Lambda
- Experience with ETL platforms such as Talend, Informatica, SSIS, or DataStage
- Experience with Agile and Scrum methodologies
- Knowledge of Java or JavaScript
Responsibilities
- Build, maintain, and optimize scalable ETL pipelines using PySpark, SQL, and Python
- Troubleshoot and resolve production data pipeline issues, performing root cause analysis and implementing long-term solutions
- Monitor and support data workflows to ensure reliability, performance, and data quality
- Develop and maintain reusable data ingestion and transformation frameworks
- Explore and implement the latest AWS technologies to enhance data capabilities and operational efficiency
- Collaborate across teams to understand business needs and propose innovative data solutions
- Participate in code reviews and contribute to continuous improvement of data engineering practices
- Ensure data quality, integrity, and security across all stages of the pipeline
- Document data flows, technical specifications, and operational procedures
- Support deployment and integration of data solutions into production environments
Benefits
- competitive compensation package
- annual bonus
- long-term incentive opportunities
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What This Job Offers
Job Type
Full-time
Career Level
Entry Level
