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 contemporary 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 (India)
🏢 Neotechie
📍 India