Data Engineer

Optum; Bengaluru; On-site; INR 1,200,000 - 2,400,000; Full time

Job summary

Optum in Bengaluru is seeking a Data Engineer with 6–10 years of experience to join on short notice. You will design and maintain scalable data pipelines, work across ETL/ELT, and collaborate with analytics teams to deliver trusted data assets.

The role emphasizes cloud data platforms (Azure/AWS/GCP), Databricks, PySpark, SQL and Python, with exposure to healthcare domain preferred. Immediate to 45 days notice, Bangalore location.

Qualifications

• Bachelor's degree or higher in CS/Engineering or related field.
• 6+ 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 analytical and problem-solving skills.
• Strong communication and stakeholder collaboration skills.
• Ability to work independently with minimal supervision and handle multiple priorities.

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 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.

Skills

Data Engineering

Python programming

SQL programming

PySpark programming

Databricks

Azure/AWS/GCP

End to End Pipeline Build

Basic Data Modeling

Health care domain exposure

GenAI Exposure

Education

Bachelor's degree in Computer Science, Data Engineering, Information Systems, Engineering, or related field

Tools

Airflow

Azure Data Factory

Cloud Composer

Job description

Hello Everyone,

Optum is hiring Data Engineer at Bangalore location who can join us on a short notice.

Primary Skills: Data Engineering, Python programming, SQL programming, Pyspark programming, Databricks, Azure / AWS / GCP, End to End Pipeline Build (Extract, Transform, Load), Basic Data Modeling, Health care domain exposure, GenAI Exposure

Experience: 6 yrs to 10 yrs

Notice Period: Immediate to 45 days

Location: Bangalore

NOTE: Healthcare Domain experience is highly preferred.

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

Required Qualifications:

• Bachelors degree in Computer Science, Data Engineering, Information Systems, Engineering, or a related field
• 6+ 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