Quest Analytics is looking to modernize and scale its data environment to make healthcare more accessible. The Senior Data Engineer will help transform existing workflows into automated, cloud-based pipelines.
Requirements
- 3–5 years of experience with ETL, data operations, and troubleshooting, preferably in Healthcare data.
- Strong SQL development skills (SSMS, stored procedures, and optimization).
- Proficiency in Python, C, or Scala (experience with pandas and NumPy is a plus).
- Solid understanding of the Azure ecosystem, especially Azure Data Factory and Azure Data Lake Storage (ADLS).
- Hands-on experience with Azure Data Factory and ADLS.
- Familiarity with Spark, Databricks, and data modeling techniques.
- Experience working with both relational databases (e.g., SQL Server) and NoSQL databases (e.g., MongoDB).
Responsibilities
- Identify, design, and implement internal process improvements (e.g., automating manual processes, optimizing data delivery, and re-designing infrastructure for scalability).
- Transform manual SQL/SSMS/stored procedure workflows into automated pipelines using Azure Data Factory.
- Write clean, reusable, and efficient code in Python (and optionally C or Scala).
- Leverage distributed data tools such as Spark and Databricks for large-scale processing.
- Review project objectives to determine and implement the most suitable technologies.
- Apply best practice standards for development, build, and deployment automation.
- Manage day-to-day operations of the data infrastructure and support engineers and analysts with data investigations.
Other
- Bachelor’s Degree in Computer Science or equivalent education/experience.
- Self-motivated, strong problem-solver, and thrives in fast-paced environments.
- Excellent troubleshooting, listening, and analytical skills.
- Customer-focused mindset with a collaborative, team-oriented approach.
- Visa sponsorship is not available at this time.
