Azure Data Engineer

1 month ago

Bangalore, India Visara Full time

Job Description :


We are seeking a highly skilled and dynamic Data Engineering Analyst to join our forward-thinking data engineering team. In this pivotal role, you will be at the heart of our data-driven initiatives, leveraging the power of Azure Databricks to drive business transformation and insights. As a key member of our team, you will bridge the gap between complex data solutions and business needs, ensuring that our data engineering projects are aligned with our strategic goals and deliver tangible value.

As our ideal candidate, you will bring a strong blend of analytical skills, technical knowledge, and a deep understanding of data engineering concepts within the Azure Databricks ecosystem. Your expertise will be crucial in shaping the direction of our data projects, from conceptualization to implementation, ensuring they not only meet but exceed our business objectives. Your role will involve collaborating closely with data scientists, engineers, and key stakeholders, translating business needs into technical solutions that are efficient, scalable, and impactful.

In this role, you will have the opportunity to work in a dynamic and fast-paced environment, with a focus on innovation and excellence. We are looking for someone who is not just adept at analyzing and interpreting data but also passionate about finding new and creative ways to solve complex business challenges using advanced data technologies. If you are a strategic thinker, a problem-solver, and a team player with a passion for leveraging technology to drive business success, we would love to hear from you

Key Responsibilities :

- Requirement Gathering and Analysis: Collect and analyze business requirements from stakeholders. This involves understanding business objectives, challenges, and expectations from the data engineering project.

- Data Exploration and Understanding: Work with business users, data scientists and engineers to explore the data available in various systems of records (including SAP). Understand the nature, quality, and structure of the data to identify how it can be best used to meet business needs.

- Translating Business Needs into Technical Specifications: Convert business requirements into detailed technical specifications for data engineering team in the form of user stories in Azure DevOps. This includes defining the scope, objectives, source schemas, transformation rules, data quality rules and data consumption patterns for the data product.

- Collaboration with Data Engineering Team: Work closely with data engineers and architects to ensure that the data solutions being developed in Azure Databricks align with business requirements and are feasible within the technical framework.

- User Acceptance Testing (UAT): Define the Acceptance test criteria /plans and Coordinate and conduct UAT to validate that the data solutions meet the business requirements and perform as expected.

- Stakeholder Communication: Regularly communicate with stakeholders about the progress, challenges, and outcomes of the data engineering project.

- Keeping Abreast with Azure Databricks Updates: Stay updated with the latest features and best practices in Azure Databricks to leverage its full potential in data engineering projects.

- Feedback and Continuous Improvement: Collect feedback from users and stakeholders and incorporate it into ongoing or future projects to continuously improve data solution.

(ref:hirist.tech)

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