Azure Senior Data Technical Specialist

Job Summary

Job Title: Senior Databricks Engineer (E3.2 Band)

About HCLTech

HCLTech is a global technology company delivering industry-leading digital, engineering, and cloud solutions. With a strong focus on innovation and customer success, HCLTech enables enterprises to transform through scalable, data-driven platforms.

Role Overview

As a Senior Databricks Engineer (E3.2), you will take end-to-end ownership of designing and delivering advanced data engineering solutions on Azure. You will play a key role in architecting scalable data pipelines, leading technical discussions, and driving best practices across projects while working closely with business stakeholders and cross-functional teams.

Key Responsibilities

Key Responsibilities

• Lead the design and implementation of enterprise-grade data solutions using Azure Databricks
• Architect and optimize end-to-end data pipelines leveraging ADF, Databricks, and Synapse
• Drive data ingestion, transformation, and integration strategies across multiple data sources
• Provide technical leadership and guidance to junior engineers and project teams
• Engage with stakeholders to understand business needs and translate them into scalable solutions
• Optimize performance, cost, and reliability of Azure data platforms
• Implement CI/CD pipelines and governance using Azure DevOps
• Ensure adherence to data quality, security, and compliance standards
• Contribute to solution architecture, design reviews, and technical decision-making

Skill Requirements

Mandatory Skills

• Strong expertise in Azure Data Engineering ecosystem:
  • Azure Databricks (advanced implementation & optimization)
  • Azure Data Factory (complex pipeline orchestration)
  • Azure Synapse Analytics
  • Azure Storage / Data Lake (ADLS Gen2)
  • Azure DevOps (CI/CD pipelines)
• Deep understanding of ETL/ELT frameworks and data modeling concepts
• Advanced proficiency in SQL and relational databases
• Strong experience in performance tuning and large-scale data processing
• Hands-on experience with Python and Spark (PySpark preferred)
• Experience in solution design and architecture discussions

Preferred Skills

• Experience working in client-facing or consulting roles
• Exposure to data governance, security, and compliance frameworks
• Knowledge of real-time/streaming data processing (Kafka/Event Hub)
• Familiarity with Agile / Scrum methodologies
• Certification in Azure Data Engineering or Databricks is a plus

Educational Qualification

• Bachelor’s degree in Computer Science / IT / related field

Other Requirements

Skill Evaluation Matrix (E3.2 Expectations)

• Databricks, ADF, Synapse, ETL, SQL → Advanced expertise (Rating: 4+)
• DevOps & Storage → Strong working knowledge (Rating: 3+)
• Python & Spark → Hands-on implementation (Rating: 3+)
• Client handling & architecture → Ownership-driven capability

1.Relevant certifications in Azure Data Factory (ADF), Azure Databricks, SQL, Python are a plus.