Databricks Data Engineer

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Job Summary

Senior Data Engineer

Key Responsibilities

• Design, develop, and maintain scalable ETL/ELT pipelines

   using Azure Data Factory, Databricks, PySpark, and SQL.
• Engineer data workflows integrating 

  structured and unstructured data

   from Azure Data Lake (ADLS Gen2), Azure Synapse, SQL Server, and external APIs.
• Implement 

  data modeling and transformation logic

   to support analytics, reporting, and ML workloads.
• Collaborate with 

  data scientists and business analysts

   to understand requirements and deliver clean, reliable, production-ready datasets.

• Optimize data storage and compute performance

   in Azure Databricks and Delta Lake environments.
• Develop and maintain 

  CI/CD pipelines for data workflows

   using Azure DevOps or GitHub Actions.
• Monitor, troubleshoot, and resolve 

  pipeline performance issues

   to ensure reliability and high availability.
• Apply 

  best practices in data governance, security, and compliance

   across workflows.
• Lead end-to-end data solutioning in Azure with a focus on performance, reliability, and scalability.
• Mentor junior engineers and provide technical leadership within the team.

Required Qualifications

• Bachelor’s in Computer Science, Engineering, or related field (or equivalent work experience).

• 7+ years of experience in Data Engineering

  , including:
• Strong hands-on expertise in 

  Databricks

   (Delta Lake, orchestration, notebooks).
• In-depth experience with 

  Azure Cloud Services

   (ADF, ADLS Gen2, Synapse, Key Vault).
• High proficiency in 

  Python, PySpark, and SQL

  .
• Experience building 

  lakehouse architectures

   and designing 

  ETL/ELT pipelines

  .
• Strong background in 

  data modeling and transformation logic

  .
• Excellent communication skills with the ability to convey technical concepts to non-technical stakeholders.

Preferred Skills & Technologies

• Experience with 

  Snowflake

   for scalable data warehousing.
• Experience with 

  data mesh architectures

   and distributed data ownership.
• Familiarity with 

  event-driven architectures

  : Azure Event Hubs, Kafka.
• Exposure to 

  Databricks Workflows, MLflow, Unity Catalog

  .
• Hands-on experience with 

  Power BI

   or other BI/visualization tools.
• Knowledge of 

  Terraform

   or other Infrastructure-as-Code (IaC) tools.

Certifications (Preferred)

• Microsoft Certified: 

  Azure Data Engineer Associate (DP-203)

• Databricks Certified Data Engineer

To Apply: