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Senior Data Engineer - Hybrid

Celebal Technologies

Navi Mumbai, Maharashtra, IN Full–Time

Azure Databricks Data Engineer Experience: 6+ Years

Fulltime

We are looking for a Data Engineer to design and build scalable, production-grade data pipelines on Azure using Databricks. The role involves working with high-volume, high-velocity enterprise data across domains such as telecom, retail, and regulatory systems (e.g., GST, eWay Bill).

You will be responsible for building reliable batch and real-time pipelines, ensuring data quality, auditability, and performance at scale.

Data Engineering & Pipeline Development

  • Design and implement end-to-end data pipelines using Azure Databricks and PySpark
  • o Azure Data Factory (ADF)

o Kafka / Azure Event Hubs

  • Implement and maintain Medallion Architecture (Bronze, Silver, Gold layers)
  • Develop reusable data models for analytics, reporting, and downstream consumption
  • Ensure data lineage, traceability, and auditability across layers

Delta Lake & Data Management

  • o MERGE (upserts), SCD Type 1/2 implementations

o Late-arriving data

Performance Optimization & Scalability

  • Troubleshoot performance bottlenecks such as:

o Data skew

Design orchestration workflows using Azure Data Factory:

Data Quality & Governance

  • Implement robust data quality checks, including:

o Data reconciliation across sources

  • Handle schema drift and evolving data contracts
  • Ensure compliance with regulatory and audit requirements

o Regulatory datasets (GST, eWay Bill, financial reporting)

o Retail / telecom data platforms

  • Ensure data consistency, reconciliation, and reporting accuracy

Strong SQL:

o Transformations and actions

o Performance tuning

Azure Data Factory (ADF)

  • Azure Data Lake Storage Gen2 (ADLS)
  • Kafka or Azure Event Hubs
  • CDC pipeline implementation
  • Data quality frameworks (e.g., Strong debugging skills in distributed data systems (Spark)
  • Experience handling production incidents and RCA (Root Cause Analysis)
  • Flexibility to work in WFO / hybrid setup

Reliable, scalable pipelines handling large-scale enterprise data

  • Reduced pipeline failures and improved data SLAs
  • High-quality, trusted datasets for business-critical reporting
  • Efficient Spark jobs with optimized cost and performance

Posted 5 Mar 2026 · Listing from OnJob.io. Create a free profile to apply and see your AI match score.

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