Experience
6 - 8 yrs
Job Location
Bengaluru, India
Vacancy
1
Designation
Data Analytics Lead
Job Type
ONSITE
Job Description
Key Responsibilities:
Design, develop, customize, and manage data integration tools, data lakes, warehouses, and analytical systems on Azure.
Build, scale, and harden data pipelines (internal & external sources) using Azure Data Factory, Azure Databricks (PySpark/Spark SQL), Azure Data Lake, Azure Synapse, and Azure SQL.
- Deploy data pipelines into production environments by enriching the model with data stored in a Data Lakes or coming directly from data sources, configuring data attributes, managing computing resources, setting up monitoring tools, etc.
- Create reusable SQL scripts for reporting, data validation, and ETL processes.
- Design, develop, and optimize complex SQL/T-SQL queries, stored procedures, and performance tuning for large-scale datasets.
- Perform data profiling, cleansing, and validation to ensure accuracy and reliability.
- Develop data models and analytical frameworks to support reporting and decision-making.
- Mentor and Build a Data Engineering Support team composed of Data Engineering Resources
Own automation, observability, and monitoring frameworks capturing operational KPIs and data quality metrics; set up alerting and runbooks.
Monitor performance & stability, triage incidents, and adapt pipelines as data/models/requirements evolve.
Implement best practices for systems integration, security (RBAC, Key Vault, RLS/OLS), performance, cost optimization, and data governance.
- Work with the Data Asset and Capability teams to identify the right data sources and understand and build and support the data architectures for optimal data extraction and transformation for key business processes.
- Test the reliability and performance of data engineering pipelines and support testing team with data validation activities
- Partner with various Azure Engineering subject matter experts including project Managers and business team to scope and build customer facing content, modules, tools and proof of concepts
- Research and cultivate in state-of-the-art data engineering methodologies, drive product innovation, and act as an Azure subject matter expert for other engineers
Apply DevOps/DataOps/Agile methodologies; manage version control (Git/Bitbucket) and CI/CD pipelines (Azure DevOps/Jenkins) for data and BI assets.
- Must have Time Management, Problem-Solving & Critical Thinking skills.
- Must have presentation and stakeholder management skills
- Leadership & People Management is mandatory.
Required Qualifications
Bachelor s degree in Engineering, Computer Science, Data Analytics, IT, or related field.
6-8 years of relevant experience across Azure Data Engineering and Power BI.
Hands-on expertise with:
o Azure Databricks (PySpark/Spark SQL), Azure Data Factory, Azure Data Lake, Azure Synapse, Azure SQL
o Data modelling, Performance Tuning
o SQL/T-SQL (complex queries, stored procedures)
- Experience of leading a Data Engineering team
- Good scripting, data modeling and programming skills
- Understanding of cloud architecture principles and best practices
- Experience in the design and build of end-to-end solutions that meet business requirements and adhere to scalability, reliability, and security standards
- Familiarity with version control systems like Bitbucket, Jenkins and DevOps practices for CI/CD pipelines
Desired Qualifications
Certifications:
o Microsoft Certified: Azure Data Engineer Associate (DP-203)
o Databricks Data Engineer Associate/Professional
- Familiarity with version control systems like Bitbucket, Jenkins and DevOps practices for CI/CD pipelines
Experience with migration & modernization (from legacy ETL/BI to Azure-native).
Preferred CPG/Supply Chain domain expertise.
- Experience with data visualization tools (Power BI preferred).
- Experience in the architecture and design of services using Azure architecture is a plus