Sr. Data Engineer

• 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.
• Monitor and report on data pipeline tasks, collaborating with teams to resolve issues quickly.
• Partner with internal teams to analyze current processes and identify efficiency opportunities.
• Participate in training and mentoring programs as assigned or required.
• Uphold Quest Analytics values and contribute to a positive company culture.
• Respond professionally and promptly to client and internal requests.
• Perform other duties as assigned.

• Bachelor’s Degree in Computer Science or equivalent education/experience.
• 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).
• 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.

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.