Data Engineer

Bill Rate-$55

Location: Whitehouse Station, NJ / Exchange Place NJ. Hybrid - 3 days a week

Duration: 6 months

Role Descriptions: Data Engineer

Essential Skills: Data Engineer

Skills: Digital : Snowflake~Digital : Databricks~Azure Data Factory Experience Required: 8-10

Data Engineer - Enterprise Data Platform / GDP Role Summary We are looking for a hands-on Data Engineer to design, build, enhance, and support scalable data pipelines within an enterprise data platform. The role will focus on integrating multiple source systems, transforming and validating data, and making trusted data available to downstream applications and consumption layers.

Key Responsibilities

• Design, develop, and maintain scalable ETL/ELT data pipelines for enterprise data sources.
• Build ingestion frameworks for batch, incremental, file, database, and API-based data feeds.
• Develop data transformations using SQL, Python and/or PySpark.
• Implement source-to-target mappings and support complex data transformation requirements.
• Develop reusable and configurable pipeline patterns to accelerate onboarding of new data sources.
• Implement data quality, reconciliation, validation, and exception-handling controls.
• Eligible to workimize pipelines for performance, scalability, reliability, and maintainability.
• Implement appropriate logging, monitoring, alerting, and restart/recovery mechanisms.
• Support automated deployment using Git and CI/CD practices.
• Troubleshoot production data/pipeline issues and perform root-cause analysis.
• Work closely with Technical Leads, architects, source-system teams, and downstream consumers.
• Participate in code reviews, technical design reviews, testing, deployment, and production support.
• Maintain appropriate technical documentation, data mappings, and operational procedures.

Must-Have Skills

• 5-8+ years of hands-on Data Engineering experience.
• Strong SQL skills, including complex querying and performance Eligible to workimization.
• Strong programming experience in Python and/or PySpark.
• Strong experience with ETL/ELT and data pipeline development.
• Experience working with cloud-based enterprise data platforms.
• Strong understanding of:

o Data ingestion and transformation

o Data modeling

o Batch and incremental processing

o APIs and system integration

o Data quality and reconciliation

o Pipeline orchestration

o Error handling and recovery

o Logging and monitoring

• Hands-on experience with Git and CI/CD.
• Experience handling large-volume enterprise datasets.
• Ability to Consultantly troubleshoot complex data issues.

Preferred Skills

• Experience with Snowflake and/or modern cloud data platforms.
• Experience with AWS or Azure data services.
• Knowledge of CDC and event/streaming-based data integration.
• Experience developing reusable data ingestion frameworks and accelerators.
• Understanding of data lineage, governance, security, and access controls.
• Insurance/Claims domain experience is highly desirable.

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