Description

Job Responsibilities include:

Lead the architecture, design, and deployment of enterprise-scale data solutions using Azure Databricks and Apache Spark.

Design, develop, and optimize scalable ETL/ELT pipelines for processing structured and unstructured data.

Collaborate with data scientists, analysts, and business stakeholders to translate requirements into effective data solutions.

Establish and enforce data engineering best practices, data governance standards, security controls, and architectural frameworks.

Design and oversee CI/CD pipelines, automation workflows, and DevOps processes for Databricks environments.

Provide technical leadership, mentorship, and guidance to engineering teams while supporting cloud-based solutions across Azure, AWS, or GCP.

Required Qualifications:

Bachelor’s degree in computer science, Information Technology, Data Engineering, or a related field.

8–10 years of experience in Data Engineering, Data Architecture, and Databricks-based solution design.

Strong hands-on experience with Databricks, Apache Spark, Delta Lake, MLflow, DBSQL, and large-scale ETL/ELT pipeline development.

Extensive experience with Azure cloud services, data modeling, CI/CD, DevOps practices, and implementing enterprise data governance and architectural standards

Key Skills

Education

Any Graduate