Job Description
Job Summary
Job Title: Senior Databricks Architect (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.
