Job Description – Data Engineer I

Job Title: Data Engineer I
Experience: 3–5 Years
Employment 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.
- Solid 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 up-to-date 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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