Summary role description:

 

Hiring for an Azure Data Lead role with a fast-growing technology services provider delivering innovative IT consulting, cloud, and digital solutions.

 

Company description:

 

Our client is a global organization with a long history and presence across multiple regions. The company works with businesses in different industries to support their technology and digital needs. It provides a range of modern solutions and services that help improve operations, enhance experiences, and enable future growth. Known for its expertise and collaborative approach, the organization continues to be a trusted partner for companies undergoing various stages of digital change.

 

Role details:

 

Title / Designation: Azure Data Lead Location: Guindy, Chennai Work mode: On-site

 

Role & responsibilities:

 

Lead the design, build, and operation of the Azure Databricks data platform, ensuring scalability, reliability, and ease of use. Implement and manage the lakehouse and Medallion architecture (Bronze, Silver, Gold) to organize data for analytics, reporting, and AI. Develop and maintain end-to-end data pipelines ingesting data from APIs, files, databases, and other internal and external sources. Ensure strong data governance, security, and compliance using Unity Catalog, including access control, lineage, and metadata management. Manage, mentor, and provide technical leadership to data engineers, enforcing best practices and supporting career development. Design and manage Delta Lake tables and Azure Data Lake storage, enabling reliable processing, incremental loads, and cost-effective storage. Optimize Databricks clusters, Spark jobs, and pipelines for performance, scalability, monitoring, and cost efficiency. Establish data quality, error handling, and observability practices, ensuring stable and trustworthy data pipelines. Build secure and resilient data solutions using Azure services such as Synapse Analytics, Key Vault, and Azure Monitor. Own CI/CD, automation, and deployment standards using Git and Azure DevOps. Collaborate with business, analytics, data science, and AI teams to deliver reusable data models and support ML, GenAI, and LLM workloads. Define an AI-ready data roadmap and advise stakeholders on data modernization, transformation, and future analytics strategy. Continuously improve the platform by tracking industry trends and recommending architectural and tooling enhancements.

 

Candidate requirements:

 

Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field. 8+ years of experience in data engineering, including at least 2 years in a technical lead or people management role. Strong hands-on expertise in Azure data engineering, including Databricks, PySpark, SQL, and core Azure data services. Proven experience designing and leading end-to-end data pipelines and lakehouse solutions, using Medallion architecture, Unity Catalog, Delta Lake, and Iceberg on Databricks. Solid understanding of big data concepts, lakehouse architectures, and cloud-based ETL orchestration. Hands-on experience with Azure services such as ADLS, Data Factory, Synapse Analytics, Key Vault, SQL Server, and Azure Monitor. Experience building CI/CD pipelines and automation using Git and Azure DevOps, with strong focus on code quality and standards. Demonstrated leadership skills, including mentoring engineers, scaling teams, and effective communication with technical and non-technical stakeholders. Strong analytical and strategic thinking abilities, with experience managing complex problems and stakeholder expectations. Experience collaborating with data science, analytics, and business teams to support ML and AI use cases, including data preparation and optimization. Ability to advise and consult on data strategy and architecture for large-scale digital transformation initiatives. Relevant Azure or Databricks certifications are preferred.

 

Selection Process:

 

Two technical interviews HR round

 

Recruiter Details:

 

[email protected]