Data Engineer -Health Care

Persistent Systems Limited; Pune District; Hybrid; INR 1,400,000 - 2,100,000; Full time

Benefits offered by this job

Insurance coverage: group term life,个人

Hybrid work environment

Job summary

Persistent Systems Limited is seeking a highly skilled Data Engineer (8–12 years) to design, develop, and maintain scalable data pipelines and cloud-native data platforms. You will work with Azure, Databricks, SQL, Python, and Generative AI to power analytics and AI/ML workloads.

The role involves building data warehouses, data lakes, and ETL/ELT processes, collaborating with stakeholders, and ensuring data quality, security, and governance across enterprise data platforms.

Qualifications

• 8 to 12 years of experience in Data Engineering, Data Warehousing, or Big Data development.
• Strong expertise in SQL and Python programming for data engineering and transformation workloads.
• Hands-on experience building and supporting large-scale ETL/ELT pipelines.
• Experience working with Azure cloud services and modern data platform architectures.
• Strong expertise in Azure Databricks, Spark, and distributed data processing frameworks.
• Experience designing and managing enterprise data lakes and cloud-based data warehouses.
• Knowledge of data modeling, data governance, data quality management, and metadata management.
• Experience supporting AI/ML initiatives through feature engineering and data pipeline development.
• Working knowledge of Generative AI concepts, Large Language Models (LLMs), and AI-enabled applications.
• Experience with Azure Data Factory, Synapse Analytics, Snowflake, or similar enterprise data platforms.
• Familiarity with CI/CD pipelines, DevOps methodologies, Infrastructure as Code, and platform automation.
• Experience working with large-scale structured and unstructured datasets.
• Understanding of data security, privacy, compliance, and governance best practices.
• Healthcare, payer/provider, claims, operations, or contact center domain experience is preferred.
• Strong analytical, troubleshooting, problem-solving, and performance optimization skills.
• Excellent communication and stakeholder management capabilities.
• Ability to collaborate effectively with business, analytics, engineering, and AI/ML teams.
• Strong ownership mindset with a focus on delivering business value through data.
• Regular usage of enterprise-approved AI tools such as GitHub Copilot, Microsoft 365 Copilot, and approved Generative AI platforms.
• Ability to utilize AI tools to improve coding productivity, documentation quality, data analysis, and engineering workflows.
• Understanding of Large Language Models (LLMs), prompt engineering concepts, and AI-assisted development practices.
• Commitment to continuous learning and adoption of emerging AI capabilities to improve delivery quality and efficiency.
• Competitive salary and benefits package
• Culture focused on talent development with quarterly growth opportunities and company-sponsored higher education and certifications
• Opportunity to work with cutting-edge technologies
• Employee engagement initiatives such as project parties, flexible work hours, and Long Service awards
• Insurance coverage: group term life, personal accident, and Mediclaim hospitalization for self, spouse, two children, and parents

Responsibilities

• Design, develop, and maintain scalable data pipelines and integration frameworks.
• Build and optimize enterprise data warehouses, data lakes, and cloud-native data platforms.
• Develop robust ETL/ELT processes using SQL, Python, Databricks, and Azure services.
• Create scalable data solutions that support business intelligence, analytics, and AI/ML workloads.
• Build and maintain data models to support reporting, operational dashboards, and advanced analytics.
• Collaborate with business stakeholders to understand data requirements and transform them into technical solutions.
• Support feature engineering and data preparation activities for Machine Learning and Generative AI use cases.
• Ensure data quality, integrity, availability, security, and platform reliability.
• Implement monitoring, automation, alerting, and operational support processes.
• Optimize data processing jobs for performance, scalability, and cost efficiency.
• Support cloud data platforms including Azure Data Factory, Synapse, Databricks, and Snowflake.
• Participate in code reviews and ensure adherence to data engineering and development best practices.
• Work with DevOps teams to implement CI/CD pipelines and Infrastructure as Code practices.
• Ensure compliance with data governance, privacy, security, and regulatory standards.
• Contribute to Agile delivery processes including sprint planning, reviews, and release activities.
• Leverage enterprise-approved AI tools to improve productivity, code quality, documentation, and analytical workflows.
• Design and maintain scalable data pipelines and enterprise data integration frameworks.
• Build and optimize data warehouses, data lakes, and cloud-based data platforms.
• Ensure high levels of data quality, availability, performance, and governance.
• Partner with analytics, AI/ML, and business teams to deliver trusted data products.
• Implement automation, monitoring, and best practices across enterprise data platforms.

Skills

SQL

Python

Azure

Databricks

Generative AI

ETL/ELT

CI/CD

DevOps

Snowflake

Azure Data Factory

Synapse Analytics

Spark

Data modeling

Data governance

Tools

Azure Databricks

Azure

SQL

Python

Databricks

Snowflake

Azure Data Factory

Synapse Analytics

Spark

Job description

We are an AI-led, platform-driven Digital Engineering and Enterprise Modernization partner, combining deep technical expertise and industry experience to help our clients anticipate what's next. Our offerings and proven solutions create a unique competitive advantage for our clients by giving them the power to see beyond and rise above. We work with many industry-leading organizations across the world, including 20 Fortune 50 companies and 4 of the 5 top banks in both the US and India, and numerous innovators across the healthcare ecosystem.

We are seeking a highly motivated Data Engineer with 8 to 12 years of experience in Data Engineering, Data Warehousing, and Big Data platform development. The ideal candidate will have strong expertise in Azure, Databricks, SQL, Python, and Generative AI technologies, along with experience building scalable and reliable data platforms that power analytics, reporting, and AI/ML initiatives.

• Location: All Persistent Locations
• Experience: 8 to 12 years
• Job Type: Full-Time Employment

What You'll Do:

• Design, develop, and maintain scalable data pipelines and integration frameworks.
• Build and optimize enterprise data warehouses, data lakes, and cloud-native data platforms.
• Develop robust ETL/ELT processes using SQL, Python, Databricks, and Azure services.
• Create scalable data solutions that support business intelligence, analytics, and AI/ML workloads.
• Build and maintain data models to support reporting, operational dashboards, and advanced analytics.
• Collaborate with business stakeholders to understand data requirements and transform them into technical solutions.
• Support feature engineering and data preparation activities for Machine Learning and Generative AI use cases.
• Ensure data quality, integrity, availability, security, and platform reliability.
• Implement monitoring, automation, alerting, and operational support processes.
• Optimize data processing jobs for performance, scalability, and cost efficiency.
• Support cloud data platforms including Azure Data Factory, Synapse, Databricks, and Snowflake.
• Participate in code reviews and ensure adherence to data engineering and development best practices.
• Work with DevOps teams to implement CI/CD pipelines and Infrastructure as Code practices.
• Ensure compliance with data governance, privacy, security, and regulatory standards.
• Contribute to Agile delivery processes including sprint planning, reviews, and release activities.
• Leverage enterprise-approved AI tools to improve productivity, code quality, documentation, and analytical workflows.
• Design and maintain scalable data pipelines and enterprise data integration frameworks.
• Build and optimize data warehouses, data lakes, and cloud-based data platforms.
• Ensure high levels of data quality, availability, performance, and governance.
• Partner with analytics, AI/ML, and business teams to deliver trusted data products.
• Implement automation, monitoring, and best practices across enterprise data platforms.

Expertise You'll Bring:

• 8 to 12 years of experience in Data Engineering, Data Warehousing, or Big Data development.
• Strong expertise in SQL and Python programming for data engineering and transformation workloads.
• Hands-on experience building and supporting large-scale ETL/ELT pipelines.
• Experience working with Azure cloud services and modern data platform architectures.
• Strong expertise in Azure Databricks, Spark, and distributed data processing frameworks.
• Experience designing and managing enterprise data lakes and cloud-based data warehouses.
• Knowledge of data modeling, data governance, data quality management, and metadata management.
• Experience supporting AI/ML initiatives through feature engineering and data pipeline development.
• Working knowledge of Generative AI concepts, Large Language Models (LLMs), and AI-enabled applications.
• Experience with Azure Data Factory, Synapse Analytics, Snowflake, or similar enterprise data platforms.
• Familiarity with CI/CD pipelines, DevOps methodologies, Infrastructure as Code, and platform automation.
• Experience working with large-scale structured and unstructured datasets.
• Understanding of data security, privacy, compliance, and governance best practices.
• Healthcare, payer/provider, claims, operations, or contact center domain experience is preferred.
• Strong analytical, troubleshooting, problem-solving, and performance optimization skills.
• Excellent communication and stakeholder management capabilities.
• Ability to collaborate effectively with business, analytics, engineering, and AI/ML teams.
• Strong ownership mindset with a focus on delivering business value through data.
• Regular usage of enterprise-approved AI tools such as GitHub Copilot, Microsoft 365 Copilot, and approved Generative AI platforms.
• Ability to utilize AI tools to improve coding productivity, documentation quality, data analysis, and engineering workflows.
• Understanding of Large Language Models (LLMs), prompt engineering concepts, and AI-assisted development practices.
• Commitment to continuous learning and adoption of emerging AI capabilities to improve delivery quality and efficiency.
• Competitive salary and benefits package
• Culture focused on talent development with quarterly growth opportunities and company-sponsored higher education and certifications
• Opportunity to work with cutting-edge technologies
• Employee engagement initiatives such as project parties, flexible work hours, and Long Service awards
• Insurance coverage: group term life, personal accident, and Mediclaim hospitalization for self, spouse, two children, and parents

Values-Driven, People-Centric & Inclusive Work Environment:

Persistent is dedicated to fostering diversity and inclusion in the workplace. We invite applications from all qualified individuals, including those with disabilities, and regardless of gender or gender preference. We welcome diverse candidates from all backgrounds.

• We support hybrid work and flexible hours to fit diverse lifestyles.
• Our office is accessibility-friendly, with ergonomic setups and assistive technologies to support employees with physical disabilities.
• If you are a person with disabilities and have specific requirements, please inform us during the application process or at any time during your employment

“Persistent is an Equal Opportunity Employer and prohibits discrimination and harassment of any kind.”