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# Azure Senior Data Lead

- **Company:** HCLTech
- **Location:** London, UK
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Data Analysis, Microsoft Azure, Big Data, Information Engineering, Data Integration, Extract Transform Load (ETL), Data Security, Data Systems, Data Warehousing, Database Development, Python (Programming Language), Oracle (Applications), Oracle SQL Developer, SQL Databases, Data Processing, Freeform SQL, Azure Data Factory, Data Pipelines, Databricks
- **Published:** August 4, 2026
- **Apply:** https://uk.indeed.com/viewjob?jk=51047ee0a232141a

## About the Role

1. Proficiency in azure data factory (adf) and azure databricks for data integration and processing.
 2. Strong skills in writing complex sql queries for data manipulation and analysis.
 3. Experience with oracle pl/sql for database development and management.
 4. Proficient in python programming language for automation and scripting tasks.
 5. Solid understanding of data warehousing concepts, etl processes, and data modeling.
 6. Ability to work in a fast paced environment and manage multiple priorities effectively.
 7. Excellent problem-solving skills and attention to detail.
 8. Strong communication and interpersonal skills for effective collaboration with team members and stakeholders.
Other Requirements
1.Relevant certifications in Azure Data Factory, Azure Databricks, SQL, Oracle, or Python would be a plus.

## Description

The Senior Technical Lead will be responsible for leading the technical aspects of projects related to Azure Data Factory (ADF), Azure Databricks, SQL, Oracle PL/SQL, and Python. The role involves designing, developing, and maintaining data pipelines and ETL processes while ensuring high performance and scalability of data solutions., 1. Lead the end-to-end technical implementation of data projects using azure data factory, azure databricks, sql, oracle pl/sql, and python.

 2. Design and develop efficient and reliable etl processes for large datasets.
 3. Collaborate with cross functional teams to understand business requirements and translate them into technical solutions.
 4. Optimize data workflows, troubleshoot issues, and ensure data quality and integrity.
 5. Implement best practices for data security, governance, and compliance.
 6. Provide technical guidance, mentoring, and support to junior team members.
 7. Stay uptodate with the latest trends and technologies in data engineering and analytics.


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