Job Summary :

Lead Azure Data Engineer with 5+ years of experience in designing and building scalable data lakes, data warehouses, and ETL pipelines using Azure Data Factory, Azure Databricks, SQL, and Python.

Responsibilities :

- Develop, implement, and maintain the information data lake and use insight platforms to enable decision support systems.

- Partner with business and customers to understand data and reporting requirements.

- Bring data sets together to answer business questions and drive growth.

- Design ETLs to ingest data into the data warehouse and data lake, as well as end-user facing reporting applications.

- Collaborate with business customers and development teams to define requirements and deliver flexible, scalable, end-to-end solutions.

- Work with new technologies while driving business intelligence solutions end-to-end: business requirements, data modelling, ETL, metadata, reporting, and dashboarding.

- Apply expertise in the design, creation, management, and business use of large datasets.

- Define SLA for all areas of ownership.

Tech Stack & Requirements:

- Experience with Data modelling, SQL, ETL, Data Warehousing and Data lakes.

- Experience in writing SQL and Python scripts.

- Experience in building dashboards and reports using Microsoft Power BI.

- Experience in transforming data using Azure Data Factory.

- Experience working with Spark and Azure Databricks.

- Ability to balance and prioritize multiple conflicting requirements with high attention to detail.

- Strong verbal/written communication & data presentation skills.

- Familiarity with scripting languages such as Python, PySpark, or JavaScript.

- Knowledge of Azure Databricks and MPP databases.

- Exposure to NoSQL databases (such as Cosmos DB, MongoDB).

- Experience following Agile processes.

- Experience working with distributed version control systems like Git.

- Experience with Mulesoft/Kingswaysoft/Marketo.