Description

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

This role is on-site.

Responsibilities

• Design and optimize scalable ETL/ELT pipelines for structured and unstructured data.
• Establish data engineering best practices, governance standards, security controls, and architectural frameworks.
• Design and oversee CI/CD pipelines, automation workflows, and DevOps processes for Databricks environments.
• Collaborate with data scientists, analysts, and stakeholders to translate requirements into effective data solutions.
• Provide technical leadership and mentorship to engineering teams across cloud-based solutions.

Required Skills

• 8–10 years of experience in Data Engineering, Data Architecture, and Databricks-based solution design.
• Hands-on expertise with Azure Databricks, Apache Spark, Delta Lake, MLflow, and DBSQL.
• Extensive experience building large-scale ETL/ELT pipelines.
• Strong knowledge of Azure cloud services, AWS, and GCP.
• Proven experience with CI/CD, DevOps practices, and data modeling.
• Bachelor’s degree in Computer Science, IT, Data Engineering, or a related field.

Preferred Skills

• Experience implementing enterprise data governance and architectural standards.

Key Skills

Education

Any Graduate