Job Details

Role Overview

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.

Responsibilities

• 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.

Required Skills

Preferred Skills

• 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.