Sr. Data Engineer
Posted 1 day ago by 1763642209
Negotiable
Outside
Remote
USA
Summary: The Sr. Data Engineer role involves designing, developing, and maintaining data pipelines for data lakes and warehouses, while collaborating with various teams to enhance data accessibility. The position requires extensive experience in data engineering and proficiency in AWS services, alongside strong coding skills. The role is remote and classified as outside IR35.
Key Responsibilities:
- Design, develop, and maintain data pipelines to extract and load data into data lakes and warehouses.
- Build and optimize data transformation rules and data models for analytical and operational use.
- Collaborate with Product Analysts, Data Scientists, and ML Engineers to make data accessible and actionable.
- Implement data quality checks, maintain data catalogs, and utilize orchestration, logging, and monitoring tools.
- Apply test-driven development methodologies to ELT/ETL pipeline construction.
Key Skills:
- 10+ years of relevant experience in data engineering.
- Domain expertise in DPTM (Discovery Preclinical and Translational Medicine) and DSCS (Development Sciences and Clinical Supply).
- Proficiency with AWS services including S3, IAM, Redshift, Sagemaker, Glue, Lambda, Step Functions, and CloudWatch.
- Hands-on experience with platforms like Databricks and Dataiku.
- Strong coding skills in Python/Java, SQL (Redshift preferred), and tools like Jenkins, CloudFormation, Terraform, Git, Docker, and Spark (2–3 years with PySpark).
Salary (Rate): undetermined
City: undetermined
Country: USA
Working Arrangements: remote
IR35 Status: outside IR35
Seniority Level: undetermined
Industry: IT
Detailed Description From Employer:
Roles and Responsibilities:
- Design, develop, and maintain data pipelines to extract and load data into data lakes and warehouses.
- Build and optimize data transformation rules and data models for analytical and operational use.
- Collaborate with Product Analysts, Data Scientists, and ML Engineers to make data accessible and actionable.
- Implement data quality checks, maintain data catalogs, and utilize orchestration, logging, and monitoring tools.
- Apply test-driven development methodologies to ELT/ETL pipeline construction.
Requirements:
- 10+ years of relevant experience in data engineering.
- Domain expertise in DPTM (Discovery Preclinical and Translational Medicine) and DSCS (Development Sciences and Clinical Supply).
- Proficiency with AWS services including S3, IAM, Redshift, Sagemaker, Glue, Lambda, Step Functions, and CloudWatch.
- Hands-on experience with platforms like Databricks and Dataiku.
- Strong coding skills in Python/Java, SQL (Redshift preferred), and tools like Jenkins, CloudFormation, Terraform, Git, Docker, and Spark (2–3 years with PySpark).