Lead Azure Data Engineer

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EXL

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Job Summary


Job Type
-

Seniority

Years of Experience
Information not provided

Tech Stacks
Python SQL Spark Azure Sprint Shell Synapse Shell Script Factory

Job Description

Role: Lead Data Engineer

Experience: 9+ years, with a minimum of 5 years Data Engineering experience on Azure

Required Skills:

  • Expert in using Azure Synapse, Azure Storage, and Azure Data Factory to build data solutions.
  • Strong understanding of metadata-driven approaches and data governance principles.
  • Excellent problem-solving skills and ability to work in a fast-paced, collaborative environment.
  • Experience with agile development methodologies and DevOps practices as the Lead Data Engineer is mandatory.
  • Extensive programming expertise with Python, Py Spark, SQL and shell scripting is essential.
  • Strong communication and interpersonal skills, with the ability to effectively interact with stakeholders at all levels.

Responsibilities:

  • Designing and implementing data engineering solutions using Azure services such as Synapse, Azure Storage, and Data Factory.
  • Providing technical direction to the team and assisting with the design and implementation of technical architecture for data solutions, ensuring scalability and performance.
  • Managing the ADO (Azure DevOps) board, including creating and tracking work items, ensuring timely updates, and facilitating smooth sprint planning and execution.
  • Engaging in problem solving and ad-hoc troubleshooting to resolve complex technical issues and acting as the primary contact for resolving issues.
  • Developing and maintaining data pipelines to efficiently extract, transform, and load data from various sources.
  • Implementing metadata-driven approaches to automate and optimize data workflows.
  • Collaborating with cross-functional teams to gather requirements and define data engineering architectures.
  • Ensuring data quality and reliability through rigorous testing and validation processes.
  • Implement monitoring frameworks for data pipelines and performance metrics to identify and address issues proactively.
  • Staying updated on emerging trends and best practices in data engineering and Azure technologies.
  • Leading teams to achieve project goals, providing guidance and mentorship to junior team members to foster growth.

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