Seeking a Data Engineer with experience building scalable data pipelines, data warehouses, and ingestion frameworks for enterprise environments. The role involves consolidating fragmented enterprise data into clean, reliable, and analytics-ready datasets while ensuring performance, governance, and data quality across cloud-based platforms.

Build and maintain ETL/ELT pipelines from enterprise source systems including EHRs, ERPs, billing platforms, and operational databases.
Design, develop, and manage scalable data warehouse and lakehouse architectures.
Implement data ingestion, transformation, validation, and orchestration workflows.
Ensure data quality, lineage, governance, and consistency across pipelines and platforms.
Collaborate with data scientists, analysts, and business teams to deliver reliable data products and reporting solutions.
Optimize pipeline performance, reliability, scalability, and cloud infrastructure costs.
Develop batch and real-time data processing workflows using modern data engineering frameworks.
Work with cloud platforms, distributed systems, and large-scale structured/unstructured datasets.
Maintain monitoring, troubleshooting, documentation, and operational support for data platforms.

Experience working with healthcare, financial, or energy sector datasets and compliance requirements.
Hands-on experience with modern data stack tools such as Snowflake, Databricks, BigQuery, or Redshift.
Familiarity with distributed data processing and orchestration frameworks.
Understanding of data governance, metadata management, and data reliability practices.
Strong analytical, troubleshooting, and collaboration skills.
Education: Bachelor's degree in Computer Science, Information Technology, Engineering, Mathematics, or a related field. Relevant cloud or data engineering certifications and enterprise data platform experience are a plus.

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Data Engineer

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