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What you will do :

As a Lead Data Engineer , you will Lead a team responsible for the build, support, and optimization modern data solutions and analytical products across the Azure Data Platform.

Youll design and manage robust data pipelines (Azure Data Factory, Azure Databricks, Data Lake, Spark.SQL). You will collaborate closely with business stakeholders, data engineers, and data scientists to maintain reliable, secure, and scalable data products that drive decision-making - particularly within Supply Chain and CPG contexts.

Key Responsibilities :

Data Engineering Development Lead :

- 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.

- Build and 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.

- 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.

- Build POCs on tool stack like Neo4j Graph db, Databricks, Fabric etc and suggest

changes for cost optimization.

- 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.

Required Qualifications :

- Bachelors 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 :

1. Azure Databricks (PySpark/Spark SQL), Azure Data Factory, Azure Data Lake, Azure

Synapse, Azure SQL

2. Data modelling, Performance Tuning

3. 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

The job is for:

Women candidates preferred