Senior Data Engineer
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Before you apply
LocationGurgaon, Haryana, India
Typefull-time
SenioritySenior
Experience3+ yrs
Company size10,000+ people
PostedNov 4, 2026 · 4d ago
Verified live1d ago
At a glanceSummarised by Seekless from the posting.
Bachelor's degree in Computer Science, Information Technology, Engineering, or related field
3+ years of experience in Data Engineering, ETL development, or Big Data platforms
3+ years of hands-on experience with Azure Databricks and PySpark development
Hands-on experience with cloud data platforms such as Azure Databricks, Azure Data Lake Storage (ADLS), and Snowflake
Experience building large-scale batch and incremental data processing solutions
Experience with orchestration and scheduling tools such as Airflow, Azure Data Factory (ADF), or equivalent platforms
Experience implementing data quality validations, monitoring, logging, and operational support processes
Knowledge of data warehousing concepts, dimensional modeling, and lakehouse architectures
Familiarity with Git-based source control and CI/CD practices
Demonstrated solid programming skills in Python, PySpark, and SQL
Demonstrated solid analytical, troubleshooting, and problem-solving skills
Demonstrated solid written and verbal communication skills with the ability to collaborate across distributed teams
Design, develop, test, and support scalable data pipelines and ETL/ELT solutions using Azure Databricks, PySpark, SQL, and cloud-native technologies
Contribute to the NHI Cloud Modernization program by migrating and modernizing legacy Teradata, DataStage, Unix, and SAS-based data processing workloads to Azure Databricks and Snowflake
Develop and maintain data ingestion, transformation, and data quality frameworks supporting Bronze, Silver, and Gold data layers within the enterprise lakehouse architecture
Build reusable and optimized PySpark components, notebooks, and workflows to process large-scale healthcare claims, membership, provider, and ancillary datasets
Implement monitoring, logging, alerting, exception handling, and operational automation to improve platform reliability and supportability
Partner with product owners, business stakeholders, architects, and data consumers to understand requirements and deliver high-quality data products
Support data governance, security, lineage, and access control processes in alignment with enterprise standards
Perform performance tuning, workload optimization, and cost management of Databricks environments and data pipelines
Participate in code reviews, technical design discussions, release activities, production support, and root-cause analysis of data platform issues
Contribute to engineering best practices including CI/CD, automated testing, documentation, and operational excellence
Leverage emerging AI-assisted engineering capabilities and automation opportunities to improve delivery speed, quality, and platform efficiency where appropriate
Design, develop, and deploy AI-powered solutions using no-code, low-code, and advanced platforms
Skills
Azure Databricks
PySpark
SQL
Azure Data Lake Storage
Snowflake
Airflow
Azure Data Factory
Git
Python
Teradata
DataStage
Unix
SAS
About the company
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.
Primary Responsibilities:
•
Design, develop, test, and support scalable data pipelines and ETL/ELT solutions using Azure Databricks, PySpark, SQL, and cloud-native technologies
•
Contribute to the NHI Cloud Modernization program by migrating and modernizing legacy Teradata, DataStage, Unix, and SAS-based data processing workloads to Azure Databricks and Snowflake
•
Develop and maintain data ingestion, transformation, and data quality frameworks supporting Bronze, Silver, and Gold data layers within the enterprise lakehouse architecture
•
Build reusable and optimized PySpark components, notebooks, and workflows to process large-scale healthcare claims, membership, provider, and ancillary datasets
•
Implement monitoring, logging, alerting, exception handling, and operational automation to improve platform reliability and supportability
•
Partner with product owners, business stakeholders, architects, and data consumers to understand requirements and deliver high-quality data products
•
Support data governance, security, lineage, and access control processes in alignment with enterprise standards
•
Perform performance tuning, workload optimization, and cost management of Databricks environments and data pipelines
•
Participate in code reviews, technical design discussions, release activities, production support, and root-cause analysis of data platform issues
•
Contribute to engineering best practices including CI/CD, automated testing, documentation, and operational excellence
•
Leverage emerging AI-assisted engineering capabilities and automation opportunities to improve delivery speed, quality, and platform efficiency where appropriate
•
Builder Responsibility:
•
Design, develop, and deploy AI-powered solutions using no-code, low-code, and advanced platforms, translating business needs into scalable applications that enhance products, workflows, and decision-making
•
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, Information Technology, Engineering, or related field
•
3+ years of experience in Data Engineering, ETL development, or Big Data platforms
•
3+ years of hands-on experience with Azure Databricks and PySpark development
•
Hands-on experience with cloud data platforms such as Azure Databricks, Azure Data Lake Storage (ADLS), and Snowflake
•
Experience building large-scale batch and incremental data processing solutions
•
Experience with orchestration and scheduling tools such as Airflow, Azure Data Factory (ADF), or equivalent platforms
•
Experience implementing data quality validations, monitoring, logging, and operational support processes
•
Knowledge of data warehousing concepts, dimensional modeling, and lakehouse architectures
•
Familiarity with Git-based source control and CI/CD practices
•
Demonstrated solid programming skills in Python, PySpark, and SQL
•
Demonstrated solid analytical, troubleshooting, and problem-solving skills
•
Demonstrated solid written and verbal communication skills with the ability to collaborate across distributed teams
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.