Design, develop, and maintain scalable data ingestion, transformation, and integration pipelines
Build and optimize ETL/ELT workflows to process structured and unstructured data from multiple sources
Analyze business and customer requirements and translate them into technical data solutions
From the employer’s posting
Primary Responsibilities:
Design, develop, and maintain scalable data ingestion, transformation, and integration pipelines
Build and optimize ETL/ELT workflows to process structured and unstructured data from multiple sources
Design, develop, and maintain scalable data ingestion, transformation, and integration pipelines
Build and optimize ETL/ELT workflows to process structured and unstructured data from multiple sources
Analyze business and customer requirements and translate them into technical data solutions
Build and optimize ETL/ELT workflows to process structured and unstructured data from multiple sources
Analyze business and customer requirements and translate them into technical data solutions
Identify and resolve non-standard data challenges and moderately complex engineering problems
Bachelor's degree in Computer Science, Data Engineering, Information Systems, Engineering, or a related field
Proven ability to work independently with minimal supervision and handle multiple priorities
3+ years of experience in data engineering, software engineering, or big data development
Experience developing ETL/ELT pipelines and working with large-scale datasets
Experience with data warehouses, data lakes, and modern data architectures
Solid proficiency in SQL and Python for data processing and engineering
Preferred experience
Experience with Databricks, Spark/PySpark, Snowflake, BigQuery, or similar cloud data technologies
Experience supporting analytics, business intelligence, or AI/ML workloads
Experience in healthcare, financial services, or other highly regulated industries
Familiarity with workflow orchestration tools such as Airflow, Azure Data Factory, or Cloud Composer
Qualification wording
Bachelor's degree in Computer Science, Data Engineering, Information Systems, Engineering, or a related field
Proven ability to work independently with minimal supervision and handle multiple priorities
3+ years of experience in data engineering, software engineering, or big data development
Experience developing ETL/ELT pipelines and working with large-scale datasets
Experience with data warehouses, data lakes, and modern data architectures
Solid proficiency in SQL and Python for data processing and engineering
Experience with Databricks, Spark/PySpark, Snowflake, BigQuery, or similar cloud data technologies
Experience supporting analytics, business intelligence, or AI/ML workloads
Experience in healthcare, financial services, or other highly regulated industries
Familiarity with workflow orchestration tools such as Airflow, Azure Data Factory, or Cloud Composer
Education & alternatives
Required Qualifications:
- Bachelor's degree in Computer Science, Data Engineering, Information Systems, Engineering, or a related field
- 3+ years of experience in data engineering, software engineering, or big data development
Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
Python
SQL
AWS
Azure
BigQuery
Databricks
GCP
Snowflake
Spark
Airflow
PySpark
Where the posting names them
- Experience with data warehouses, data lakes, and modern data architectures
- Solid proficiency in SQL and Python for data processing and engineering
- Knowledge of cloud-based data platforms such as Azure, AWS, or Google Cloud
- Solid proficiency in SQL and Python for data processing and engineering
- Knowledge of cloud-based data platforms such as Azure, AWS, or Google Cloud
- Understanding of data modeling, data quality, and data governance principles
Preferred Qualifications:
- Cloud platform certifications in Azure, AWS, or GCP
- Experience with Databricks, Spark/PySpark, Snowflake, BigQuery, or similar cloud data technologies
- Experience in healthcare, financial services, or other highly regulated industries
- Familiarity with workflow orchestration tools such as Airflow, Azure Data Factory, or Cloud Composer
At UnitedHealth Group, our mission is to help people live healthier lives and make the health system work better for everyone. We believe everyone-of every race, gender, sexuality, age, location and income-deserves the opportunity to live their healthiest life. Today, however, there are still far too many barriers to good health which are disproportionately experienced by people of color, historically marginalized groups and those with lower incomes. We are committed to mitigating our impact on the environment and enabling and delivering equitable care that addresses health disparities and improves health outcomes - an enterprise priority reflected in our mission.
- Cloud platform certifications in Azure, AWS, or GCP
- Experience with Databricks, Spark/PySpark, Snowflake, BigQuery, or similar cloud data technologies
- Experience supporting analytics, business intelligence, or AI/ML workloads
Complete your application on careers.unitedhealthgroup.com. The employer’s form will show what is required.
Applying through Radancy (TalentBrew)
Radancy (TalentBrew) runs the employer’s careers site, but the application itself usually runs on another system, often Workday or Taleo. The advice for that system applies once you click Apply.
Yes. We’ve followed one other Associate Data Engineering Manager job there since May 2026. It came down after 13 days.
NoidaCame down after 13 days, first seen May 28
This jobUp 88 days so far, first seen Aug 18
May 28Today
About UnitedHealth Group
People
About 390,000 in 2025, down 2% from the year before.Annual report (SEC Form 10-K)
Company
Listed as UNH.
H-1B visas
11 approved for new hires in fiscal 2025.US Citizenship and Immigration Services
Demand for Data Leadership roles
New Data Leadership postings at the employers we follow are about the same over the last 6 weeks compared with the 6 before.
August 17Last week
Each bar is one week of new postings. The darkest bars are the last 6 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
About the role
We file this job under Data Leadership, by the work the posting describes.
Data leaders run data teams or design how a company's data fits together. Managers hire, set priorities and answer for whether the data work pays off; architects choose the systems and the shape of the data.
Expect years of hands-on data work, experience leading people or projects, and the ability to explain tradeoffs to executives.
Unlike a senior engineer or analyst, most of a data leader's week goes to people, planning and decisions rather than building.
US government figures for computer and information systems managers
Median yearly pay, May 2025
$175,140
Expected change, 2025 to 2035
15.8% more jobsagainst 3.5% for all jobs
The government has no code for data leaders, so these figures are for the closest group, computer and information systems managers, which includes data processing and data operations managers.
Optum is a global organization that delivers care, aided by technology to help millions of people live healthier lives. The work you do with our team will directly improve health outcomes by connecting people with the care, pharmacy benefits, data and resources they need to feel their best. Here, you will find a culture guided by inclusion, talented peers, comprehensive benefits and career development opportunities. Come make an impact on the communities we serve as you help us advance health optimization on a global scale. Join us to start Caring. Connecting. Growing together.
The Data Engineer (SG27) is responsible for designing, developing, and maintaining scalable data pipelines and data platforms that enable analytics, reporting, and AI/ML solutions. This role works independently on moderately complex data engineering challenges, partners with business and technology stakeholders to understand requirements, and develops reliable data solutions that support enterprise data needs. The Data Engineer serves as a technical resource to team members, provides guidance on best practices, and contributes to the continuous improvement of data platforms and engineering processes.
Primary Responsibilities:
Design, develop, and maintain scalable data ingestion, transformation, and integration pipelines
Build and optimize ETL/ELT workflows to process structured and unstructured data from multiple sources
Analyze business and customer requirements and translate them into technical data solutions
Identify and resolve non-standard data challenges and moderately complex engineering problems
Develop and maintain data models, data quality frameworks, and validation processes
Collaborate with data analysts, data scientists, product teams, and business stakeholders to deliver trusted data assets
Monitor and optimize pipeline performance, reliability, scalability, and cost efficiency
Support cloud-based data platforms and data warehouse/lakehouse environments
Implement data governance, security, lineage, and compliance standards across data assets
Create technical documentation, design specifications, and operational procedures
Provide technical guidance and knowledge sharing to junior engineers and team members
Participate in code reviews and promote engineering best practices for development, testing, and deployment
Troubleshoot production issues, perform root-cause analysis, and implement sustainable solutions
Contribute to automation, CI/CD processes, and continuous improvement initiatives across the data ecosystem
Comply with the terms and conditions of the employment contract, company policies and procedures, and any and all directives (such as, but not limited to, transfer and/or re-assignment to different work locations, change in teams and/or work shifts, policies in regards to flexibility of work benefits and/or work environment, alternative work arrangements, and other decisions that may arise due to the changing business environment). The Company may adopt, vary or rescind these policies and directives in its absolute discretion and without any limitation (implied or otherwise) on its ability to do so
Required Qualifications:
Bachelor's degree in Computer Science, Data Engineering, Information Systems, Engineering, or a related field
3+ years of experience in data engineering, software engineering, or big data development
Experience developing ETL/ELT pipelines and working with large-scale datasets
Experience with data warehouses, data lakes, and modern data architectures
Solid proficiency in SQL and Python for data processing and engineering
Knowledge of cloud-based data platforms such as Azure, AWS, or Google Cloud
Understanding of data modeling, data quality, and data governance principles
Proven solid analytical and problem-solving skills
Proven excellent communication and stakeholder collaboration skills
Proven ability to work independently with minimal supervision and handle multiple priorities
Preferred Qualifications:
Cloud platform certifications in Azure, AWS, or GCP
Experience with Databricks, Spark/PySpark, Snowflake, BigQuery, or similar cloud data technologies
Experience supporting analytics, business intelligence, or AI/ML workloads
Experience in healthcare, financial services, or other highly regulated industries
Familiarity with workflow orchestration tools such as Airflow, Azure Data Factory, or Cloud Composer
At UnitedHealth Group, our mission is to help people live healthier lives and make the health system work better for everyone. We believe everyone-of every race, gender, sexuality, age, location and income-deserves the opportunity to live their healthiest life. Today, however, there are still far too many barriers to good health which are disproportionately experienced by people of color, historically marginalized groups and those with lower incomes. We are committed to mitigating our impact on the environment and enabling and delivering equitable care that addresses health disparities and improves health outcomes - an enterprise priority reflected in our mission.