Description

You will design and maintain the organization's data lake and warehouse, enabling decision support systems and driving growth through data.

Responsibilities

• Design ETL pipelines to ingest data into the data warehouse and data lake, supporting end-user reporting applications.
• Partner with business stakeholders to define requirements, translate them into data models, and deliver scalable end-to-end solutions.
• Build and maintain dashboards and reports using Microsoft Power BI to answer business questions.
• Define and enforce SLAs for data ownership areas, ensuring reliability and performance.
• Cleanse and transform large datasets using Azure Data Factory, Spark, and Azure Databricks.

Required Skills

• 8+ years of experience in data engineering, with strong proficiency in SQL and Python.
• Deep understanding of data modeling, ETL processes, data warehousing, and data lake architecture.
• Hands-on experience with Microsoft Power BI for dashboarding and reporting.
• Proficiency in Azure Data Factory for data transformation and orchestration.
• Experience working with Spark and Azure Databricks in distributed environments.
• Familiarity with NoSQL databases such as Cosmos DB and MongoDB.
• Strong verbal and written communication skills with the ability to present data findings to technical and business teams.

Preferred Skills

• Experience with Mulesoft, Kingswaysoft, or Marketo.
• Familiarity with JavaScript or PySpark scripting.
• Experience with distributed version control systems (Git) and Agile processes.

Key Skills

Education

Any Gradute