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