Data Engineer 2

Job Title: Data Engineer IExperience: 3–5 YearsEmployment Type: Full-Time

Role Summary

We are seeking skilled Data Engineer I professionals to support enterprise data engineering and advanced analytics initiatives. The role will focus on designing, developing, maintaining, and supporting data pipelines, ETL/ELT processes, and analytics workflows across modern data platforms.

The ideal candidate will have strong foundational experience in data engineering, SQL, data transformation, cloud data platforms, and data quality practices. The candidate should be comfortable working with large datasets, supporting investigative analytics use cases, and collaborating with global teams in a managed services environment.

Key Responsibilities

Design, develop, test, and maintain scalable ETL/ELT pipelines supporting enterprise data processing and analytics requirements.

Perform data ingestion, extraction, transformation, and integration across multiple datasets and business domains.

Develop and optimize SQL queries for data processing, reporting, and analytical workloads.

Support data platform operations, production processes, and ongoing enhancements.

Collaborate with business, analytics, and data teams to:

Explore and analyze enterprise datasets.

Support investigative analytics initiatives such as fraud, waste, and abuse (FWA) analysis.

Enable data discovery and analytical workflows.

Work with modern data platforms and productivity-enhancing tools to accelerate analysis while ensuring accuracy and reliability of outputs.

Implement data validation checks and ensure data quality, consistency, and completeness across pipelines and datasets.

Monitor pipeline performance, troubleshoot failures, and resolve data-related issues.

Contribute to continuous improvement of data models, workflows, and engineering processes.

Support both production and non-production environments.

Participate in technical discussions, code reviews, documentation, and knowledge-sharing activities.

Collaborate effectively with offshore and global delivery teams.

Required QualificationsEducation

Bachelor’s degree in Computer Science, Information Technology, Engineering, Data Science, or a related field.

Experience

3–5 years of experience in Data Engineering or related roles.

Hands-on experience developing and supporting enterprise-scale data pipelines.

Experience working with large datasets and complex data processing environments.

Experience supporting analytics and reporting solutions.

Required Technical SkillsData Engineering

Strong understanding of ETL/ELT concepts and data engineering practices.

Experience designing and maintaining data pipelines.

Strong SQL skills including:

Complex queries

Query optimization

Data transformation

Data validation

Data Platforms

Experience with modern data platforms such as:

Snowflake or cloud-based data warehouses

Distributed data processing frameworks

Data lake and analytics platforms

Data Transformation & Processing

Experience with data transformation frameworks.

Understanding of data modeling concepts.

Ability to process and analyze structured and semi-structured data.

Data Quality & Validation

Experience implementing data quality checks.

Ability to validate datasets and analytical outputs.

Strong debugging and troubleshooting skills.

Analytics Support

Ability to support data exploration and investigative analysis.

Understanding of analytical workflows and business reporting requirements.

Exposure to AI-assisted or code-assisted analytics tools is preferred.

Preferred Qualifications

Experience supporting Fraud, Waste, and Abuse (FWA) analytics or similar investigative data use cases.

Healthcare domain experience, including:

Claims data

Provider data

Clinical data

Healthcare analytics platforms

Familiarity with AI-enabled data engineering or analytics productivity tools.

Experience with cloud data platforms and modern analytics ecosystems.

Exposure to data pipeline orchestration tools such as Airflow, Azure Data Factory, or similar platforms.

Experience working in offshore delivery, managed services, or long-term production support environments.

Key Competencies

Data Engineering Fundamentals

ETL/ELT Development

SQL Development & Optimization

Data Pipeline Support

Data Quality Management

Data Analysis & Investigation

Problem Solving & Debugging

Cloud Data Platform Knowledge

Collaboration with Global Teams

Documentation & Knowledge Sharing

Production Support Mindset

Role Benefits

Opportunity to work on enterprise-scale data engineering and analytics initiatives.

Exposure to modern cloud data platforms and AI-enabled analytics capabilities.

Collaboration with global teams across data engineering, analytics, and business functions.

Opportunity to contribute to healthcare and business intelligence solutions.

Work Location: Hybrid remote in Noida, Uttar Pradesh (Noida)

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