Data Engineer 3

WebSenor Ltd; Bengaluru; Hybrid; INR 1,500,000 - 3,000,000; Full time

Job summary

WebSenor Ltd in Noida, Uttar Pradesh, is seeking an experienced Data Engineer to design, develop, and optimize scalable data pipelines for healthcare analytics, AI/ML initiatives, and reporting modernization.

The role emphasizes building enterprise data models, ETL/ELT pipelines using Snowflake, Azure Data Factory, and Azure Databricks, while ensuring data quality, governance, and security across data platforms.

Qualifications

• Bachelor's degree in CS/IT/Engineering or related field.
• 5–8 years of Data Engineering experience in enterprise settings.
• Experience with cloud data platforms and modern analytics ecosystems.
• Strong SQL, Python, and data modeling skills.

Responsibilities

• Design, develop, test, and maintain scalable ETL/ELT pipelines.
• Build and optimize data ingestion using Snowflake, ADF, Databricks and cloud tech.
• Integrate healthcare data sources including claims, membership, provider data.
• Develop enterprise data models for reporting, analytics, BI, and AI/ML.
• Ensure data quality, governance, security, and compliance standards.
• Optimize SQL queries and data processing performance.
• Collaborate with Data Architects/Scientists and participate in Agile.

Skills

SQL

Python

Data Pipelines

Data Warehousing

ETL/ELT

Cloud Platforms

Education

Bachelor's degree in Computer Science / IT / Engineering

Tools

Snowflake

Azure Data Factory

Azure Databricks

Power BI

Job description

Job Title: Data Engineer

Experience: 5–8 Years

Employment Type: Full-Time

Role Summary

We are seeking an experienced Data Engineer to support enterprise healthcare data platforms, AI/ML initiatives, reporting modernization, and cloud-based data engineering programs. The ideal candidate will have strong expertise in designing, developing, and optimizing scalable data pipelines, building modern data warehouse solutions, and integrating diverse healthcare data sources.

The candidate will collaborate with Data Architects, Data Scientists, Business Analysts, and engineering teams to deliver secure, reliable, and high-performance data solutions that support analytics, reporting, and AI/ML use cases.

Key Responsibilities

• Design, develop, test, and maintain scalable ETL/ELT pipelines for enterprise data platforms.
• Build and optimize data ingestion frameworks using Snowflake, Azure Data Factory, Databricks, and cloud-based technologies.
• Integrate data from multiple healthcare source systems including claims, membership, provider, and clinical data platforms.
• Develop and maintain enterprise data models supporting:
  • Reporting
  • Analytics
  • Business intelligence
  • AI/ML solutions
• Perform data transformation, cleansing, validation, and enrichment activities.
• Ensure data quality, governance, security, and compliance standards are followed across data solutions.
• Develop efficient SQL queries and optimize data processing performance.
• Support reporting modernization initiatives, including migration from legacy reporting platforms.
• Collaborate with Data Architects and Data Scientists to prepare and optimize datasets for advanced analytics and machine learning workflows.
• Troubleshoot data pipeline failures, performance issues, and production data processing challenges.
• Implement data engineering best practices for scalability, reliability, and maintainability.
• Participate in Agile ceremonies, technical discussions, code reviews, and release activities.
• Maintain documentation related to data pipelines, architecture, processes, and operational procedures.

Required Qualifications

• Education
  • Bachelor’s degree in Computer Science, Information Technology, Engineering, Data Science, or a related field.
• Experience
  • 5–8 years of experience in Data Engineering roles.
  • Experience building enterprise-scale data pipelines and data warehouse solutions.
  • Experience working with cloud-based data platforms and modern analytics ecosystems.
  • Strong understanding of data engineering concepts, architecture, and best practices.

Required Technical Skills

• Programming & Database Technologies
  • Strong programming skills in:
    • SQL
    • Python
  • Experience with:
    • Complex SQL queries
    • Data transformation logic
    • Query optimization
    • Data validation processes
• Cloud Data Platforms
  • Hands-on experience with one or more:
    • Snowflake
    • Azure Data Factory (ADF)
    • Azure Databricks
    • Azure Cloud data services
    • Similar cloud-based data engineering platforms
• Data Engineering
  • Strong understanding of:
    • ETL/ELT frameworks
    • Data pipeline development
    • Data ingestion frameworks
    • Data warehouse concepts
    • Data modeling
    • Data integration patterns
    • Data quality management
• DevOps & Engineering Practices
  • Experience with:
    • Git
    • CI/CD pipelines
    • Agile development methodologies
    • Source control best practices
    • Production support processes

Desired Skills

• Healthcare domain experience, including:
  • Claims data
  • Membership data
  • Provider data
  • Clinical data
  • Healthcare analytics platforms
• Exposure to AI/ML data preparation workflows.
• Experience preparing datasets for machine learning models.
• Experience with reporting and visualization tools such as:
  • Power BI
  • Tableau
• Knowledge of healthcare data governance, privacy, and compliance requirements.
• Experience with cloud data modernization initiatives.

Key Competencies

• Data Pipeline Development
• Cloud Data Engineering
• Snowflake Development
• SQL & Python Programming
• Data Modeling
• Healthcare Data Analytics
• Data Quality & Governance
• Performance Optimization
• Problem Solving
• Collaboration & Communication
• Agile Delivery

Role Outcomes

The successful candidate will:

• Build and maintain scalable healthcare data platforms.
• Enable analytics, reporting, and AI/ML initiatives through reliable data solutions.
• Modernize legacy reporting and data processing workflows.
• Improve data quality, accessibility, and performance across enterprise data ecosystems.

Work Location: Hybrid remote in Noida, Uttar Pradesh