Job Description – Data Engineer (Enterprise Data Engineering & Analytics)Job Title
Data Engineer – Enterprise Data Platform & Analytics
Experience
5+ Years
Employment Type
Full-Time
Work Mode
Offshore / Remote
Job Summary
We are seeking experienced Data Engineers to support ongoing enterprise data engineering and advanced analytics initiatives. The role will focus on building, maintaining, and optimizing enterprise data pipelines, supporting analytics workflows, and enabling data-driven business solutions.
The ideal candidate will have strong expertise in ETL/ELT development, SQL, data transformation, cloud data platforms, and large-scale data processing. The candidate should be comfortable working in modern analytics environments that leverage advanced data tools, automation, and AI-assisted capabilities for data exploration and productivity improvement.
This role will support long-term steady-state operations, production data platforms, and continuous enhancement of enterprise data solutions.
Key Responsibilities
- Design, develop, test, and maintain scalable ETL/ELT pipelines for enterprise data processing and analytics.
- Perform data ingestion, transformation, integration, and validation across multiple data sources and business domains.
- Develop and optimize SQL queries, data transformations, and data processing workflows.
- Support enterprise analytics, reporting, and investigative data analysis initiatives.
- Collaborate with business analysts, data scientists, and analytics teams to:
- Explore enterprise datasets.
- Enable investigative analytics use cases.
- Support fraud, waste, and abuse (FWA) analysis.
- Validate analytical outputs and business insights.
- Ensure data quality, accuracy, reliability, and performance of data pipelines and datasets.
- Implement data validation rules, quality checks, and monitoring processes.
- Troubleshoot data pipeline issues and provide production support.
- Enhance existing data models, workflows, and data processing frameworks.
- Support both production and non-production environments.
- Participate in continuous improvement initiatives for enterprise data platforms.
- Collaborate with global teams in an offshore delivery and support model.
Required SkillsData Engineering
- Enterprise Data Engineering
- ETL/ELT Development
- Data Pipeline Development
- Data Ingestion
- Data Transformation
- Data Integration
- Large-Scale Data Processing
- Data Quality Validation
SQL & Data Processing
- Advanced SQL Development
- Query Optimization
- Data Analysis
- Data Transformation Frameworks
- Complex Data Manipulation
Data Platforms
Experience with modern data platforms including:
- Snowflake
- Cloud Data Warehouses
- Distributed Data Processing Frameworks
- Enterprise Analytics Platforms
Data Engineering Practices
- Data Quality Frameworks
- Data Validation Techniques
- Debugging and Troubleshooting
- Performance Optimization
- Production Support
- Agile Delivery Practices
Preferred Skills
- Experience with cloud data platforms such as:
- Microsoft Azure
- AWS
- Google Cloud Platform
- Experience with data pipeline orchestration tools.
- Familiarity with modern data engineering frameworks.
- Exposure to AI-assisted data engineering and analytics tools.
- Experience using productivity tools for:
- Data exploration
- Code assistance
- Automated analysis workflows
- Knowledge of healthcare data domains including:
- Claims Data
- Provider Data
- Clinical Data
- Member Data
- Experience supporting fraud, waste, and abuse (FWA) analytics.
- Experience working in managed services or long-term support environments.
Required Qualifications
- Bachelor's degree in Computer Science, Information Technology, Engineering, Data Science, or related field.
- 5+ years of experience in data engineering roles.
- Strong hands-on experience developing enterprise ETL/ELT solutions.
- Strong SQL programming and optimization skills.
- Experience working with large-scale enterprise datasets.
- Ability to analyze data, troubleshoot issues, and validate results.
- Strong communication and collaboration skills.
- Ability to work effectively with distributed global teams.
Preferred Qualifications
- Experience with healthcare, insurance, or financial services data.
- Cloud data engineering certifications.
- Experience with Snowflake, Databricks, or similar modern data platforms.
- Knowledge of AI/ML-enabled analytics workflows.
Success Measures
- Reliable operation and support of enterprise data pipelines.
- Improved data quality, availability, and processing efficiency.
- Successful delivery of analytics and investigative data solutions.
- Effective troubleshooting and resolution of production issues.
- Strong collaboration with global engineering and analytics teams.
Work Location: Hybrid remote in Remote
