Data Engineer 3

Job Title: Data EngineerExperience: 5–8 YearsEmployment 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 QualificationsEducation

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 SkillsProgramming & 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

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