DE&A - Core - Cloud Data Engineering - Azure Data Engineering

On-siteSeniorData Engineerposted 1mo ago

✦Role summaryAI-generated

This senior data engineer will architect end‑to‑end data solutions on Azure using Databricks, Delta Lake, and Spark, building scalable ETL/ELT pipelines for large volumes of data. They will also optimize performance and cost, enforce governance and security controls, and automate deployment and monitoring to support data‑driven decision‑making across the organization.

Skills required

Databricks Azure Delta Lake Spark ETL Data governance Performance tuning Automation Data pipelines Data engineering Data architecture ELT CI/CD DevOps Scala SQL Python Data modeling Data warehousing

About this role

Zensar Technologies Limited is seeking a highly skilled Senior Data Engineer with deep expertise in Databricks, Azure, Delta Lake, and Spark. In this role you will architect end‑to‑end data solutions, develop robust data pipelines, and enable data‑driven decision‑making across the organization while adhering to modern data engineering best practices.

Responsibilities

Design and implement scalable data architectures on Azure using Databricks, Delta Lake, and Spark.
Develop, test, and maintain ETL/ELT pipelines that ingest and transform large volumes of data.
Collaborate with data scientists, analysts, and business stakeholders to translate requirements into technical solutions.
Optimize performance and cost of data workloads through tuning, caching, and resource management.
Implement data governance, security, and compliance controls in line with enterprise standards.
Automate deployment and monitoring of data pipelines using CI/CD tools and Azure DevOps.
Create and maintain comprehensive documentation for data models, pipelines, and processes.
Mentor junior engineers and promote best practices in data engineering and cloud services.
Evaluate emerging technologies and recommend enhancements to the data platform.
Troubleshoot and resolve production issues, ensuring high availability and reliability.

Qualifications

5+ years of hands‑on experience in data engineering, with at least 3 years focused on Databricks and Azure.
Strong proficiency in Spark (PySpark/Scala) and Delta Lake for large‑scale data processing.
Deep understanding of Azure services such as Azure Data Lake Storage, Azure Synapse, Azure Functions, and Azure DevOps.
Experience designing and implementing ETL/ELT pipelines using modern orchestration tools.
Proficiency in SQL and programming languages like Python or Scala.
Knowledge of data modeling, data warehousing concepts, and best practices for data governance.
Demonstrated ability to optimize performance and cost in cloud environments.
Excellent problem‑solving skills and ability to work in a fast‑paced, collaborative team.
Strong communication skills to convey technical concepts to non‑technical stakeholders.
Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.