Sr. Data Engineer Job at Quest Analytics, Overland Park, KS

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  • Quest Analytics
  • Overland Park, KS

Job Description

Job Description

Job Description

At Quest Analytics, our mission is to make healthcare more accessible for all Americans. As part of our team, you’ll work in an innovative, collaborative, challenging, and flexible environment that supports your personal growth every day. We are looking for a talented and motivated Senior Data Engineer with experience in building scalable infrastructure, implementing automation, and enabling cross-functional teams with reliable and accessible data.

The Senior Data Engineer will help modernize and scale our data environment. This person will play a key role in transforming these workflows into automated, cloud-based pipelines using Azure Data Factory, Databricks, and modern data platforms. If you are looking for a high-impact opportunity to shape how data flows across the business, APPLY TODAY!

What you'll do:
  • 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.
What it requires:
  • 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 are not currently engaging with outside agencies on this role.

Visa sponsorship is not available at this time.

What you’ll appreciate:

•Workplace flexibility – you choose between remote, hybrid or in-office

•Company paid employee medical, dental and vision

•Competitive salary and success sharing bonus

•Flexible vacation with no cap, plus sick time and holidays

•An entrepreneurial culture that won’t limit you to a job description

•Being listened to, valued, appreciated -- and having your contributions rewarded

•Enjoying your work each day with a great group of people

 

Apply TODAY!

careers.questanalytics.com

About Quest Analytics

For more than 20 years, we’ve been improving provider network management one groundbreaking innovation at a time. 90% of America’s health plans use our tools, including the eight largest in the nation. Achieve your personal quest to build a great career here. 

 

Visa sponsorship is not available at this time.

Preferred work locations are within one of the following states: Alabama, Arizona, Arkansas, Colorado, Connecticut, Delaware, Florida, Georgia, Idaho, Illinois (outside of Chicago proper), Indiana, Iowa, Kansas, Kentucky, Louisiana, Maine, Maryland, Massachusetts, Michigan, Minnesota, Mississippi, Missouri, Montana, Nebraska, Nevada, New Hampshire, New Mexico, North Carolina, North Dakota, Ohio, Oklahoma, Oregon, South Carolina, South Dakota, Tennessee, Texas, Utah, Vermont, Virginia, West Virginia, Wisconsin, or Wyoming.

 

Quest Analytics provides equal employment opportunities to all people without regard to race, color, religion, sex, national origin, ancestry, marital status, veteran status, age, disability, sexual orientation or gender identity or expression or any other legally protected category. We are committed to creating and maintaining a workforce environment that is free from any form of discriminations or harassment. 

 

Applicants must be legally authorized to work in the United States. Verification of employment eligibility will be required at the time of hire.

Persons with disabilities who anticipate needing accommodations for any part of the application process may contact, in confidence hr@questanalytics.com

NOTE: Staffing agencies, headhunters, recruiters, and/or placement agencies, please do not contact our hiring managers directly. We are not currently working with additional outside agencies at this time.

  Any job posting displayed on websites other than questanalytics.com or jobs.lever.co/questanalytics/ may be out of date, inaccurate and unavailable

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.

Job Tags

Work at office, Remote work, Flexible hours,

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