Azure Data Analyst

Infosys
Leeds
3 weeks ago
Applications closed

Related Jobs

View all jobs

Azure Data Analyst: Legacy Migrations & Power BI Insights

Senior Consultant_ Data Analyst

Senior Consultant_ Data Analyst

Technical Data Analyst

Data Analysts ITSM and Azure Data Platform

Data Analysts – ITSM & Azure Data Platform

Overview

Compensation – Competitive (including bonus)

Job Description

Today, the corporate landscape is dynamic, and the world ahead is full of possibilities! None of the amazing things we do at Infosys would be possible without an equally amazing culture, the environment where ideas can flourish and where you are empowered to move forward as far as your ideas will take you.

At Infosys, we assure that your career will never stand still, we will inspire you to build what’s next and we will navigate further together. Our journey of learnability, values and trusted relationships with our clients continue to be the cornerstones of our organization and these values are upheld only because of our people.

Your Role

As an Azure & Microsoft Fabric Lead Developer, you will lead the design and development of enterprise‑grade data pipelines, lakehouses, and analytics solutions using Azure Data Services and Microsoft Fabric for client program. You will be responsible for building scalable ingestion, transformation, governance, and reporting layers aligned to client standards, workforce analytics requirements, and Trust‑level data governance.

You will collaborate closely with architects, SMEs, BI developers, data engineers, platform teams, and external partners (Microsoft) to ensure high‑quality delivery of modern analytics platforms.

Responsibilities
  • As an Azure & Microsoft Fabric Lead Developer, lead the design and development of enterprise‑grade data pipelines, lakehouses, and analytics solutions using Azure Data Services and Microsoft Fabric for client programs.
  • Build scalable ingestion, transformation, governance, and reporting layers aligned to client standards and workforce analytics requirements.
  • Collaborate with architects, SMEs, BI developers, data engineers, platform teams, and external partners to ensure high‑quality delivery of modern analytics platforms.
Required
  • Proven experience designing and developing solutions using Microsoft Fabric:
    • Lakehouse
    • Dataflows Gen2
    • Warehouse (SQL Endpoint)
    • OneLake governance
  • Ability to translate business requirements into technical architecture and detailed design.
  • Expertise in building scalable ingestion frameworks (batch/streaming) using ADF, Databricks or Fabric pipelines.
  • Strong programming skills in PySpark, SQL, Python.
  • Hands-on experience with DQ frameworks, validation rules and reconciliation logic.
  • Ability to integrate Azure/Fabric datasets with Power BI semantic models and dashboards
  • Experience building reusable datasets for Client domains such as HR, Payroll, Workforce, Clinical, or Operational reporting
  • Experience with CI/CD using Azure DevOps (Repos, Pipelines, Release Management)
  • Ability to work with data architects, platform teams and product owners to deliver high-quality designs
Preferred
  • Experience delivering technology programs within healthcare organizations in Data.
  • Experience delivering analytics in Microsoft Fabric for enterprise-scale healthcare clients
  • Experience with Fabric Admin Center, OneSecurity model, Capacity planning.
  • Certifications:
    • Fabric Analytics Engineer Associate
    • Azure Solutions Architect / Databricks certifications
  • Exposure to secure landing zones, data masking, PII handling, and access governance.
Overview

Infosys is a global leader in next-generation digital services and consulting. We enable clients in more than 50 countries to navigate their digital transformation.

With over four decades of experience in managing the systems and workings of global enterprises, we expertly steer our clients through their digital journey. We do it by enabling the enterprise with an AI-powered core that helps prioritize the execution of change. We also empower the business with agile digital at scale to deliver unprecedented levels of performance and customer delight. Our always-on learning agenda drives their continuous improvement through building and transferring digital skills, expertise, and ideas from our innovation ecosystem.

All aspects of employment at Infosys are based on merit, competence and performance. We are committed to embracing diversity and creating an inclusive environment for all employees. Infosys is proud to be an equal opportunity employer.


#J-18808-Ljbffr

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Careers

How Many Data Science Tools Do You Need to Know to Get a Data Science Job?

If you’re trying to break into data science — or progress your career — it can feel like you are drowning in names: Python, R, TensorFlow, PyTorch, SQL, Spark, AWS, Scikit-learn, Jupyter, Tableau, Power BI…the list just keeps going. With every job advert listing a different combination of tools, many applicants fall into a trap: they try to learn everything. The result? Long tool lists that sound impressive — but little depth to back them up. Here’s the straight-talk version most hiring managers won’t explicitly tell you: 👉 You don’t need to know every data science tool to get hired. 👉 You need to know the right ones — deeply — and know how to use them to solve real problems. Tools matter, but only in service of outcomes. So how many data science tools do you actually need to know to get a job? For most job seekers, the answer is not “27” — it’s more like 8–12, thoughtfully chosen and well understood. This guide explains what employers really value, which tools are core, which are role-specific, and how to focus your toolbox so your CV and interviews shine.

Jobs

What Hiring Managers Look for First in Data Science Job Applications (UK Guide)

If you’re applying for data science roles in the UK, it’s crucial to understand what hiring managers focus on before they dive into your full CV. In competitive markets, recruiters and hiring managers often make their first decisions in the first 10–20 seconds of scanning an application — and in data science, there are specific signals they look for first. Data science isn’t just about coding or statistics — it’s about producing insights, shipping models, collaborating with teams, and solving real business problems. This guide helps you understand exactly what hiring managers look for first in data science applications — and how to structure your CV, portfolio and cover letter so you leap to the top of the shortlist.

Education

The Skills Gap in Data Science Jobs: What Universities Aren’t Teaching

Data science has become one of the most visible and sought-after careers in the UK technology market. From financial services and retail to healthcare, media, government and sport, organisations increasingly rely on data scientists to extract insight, guide decisions and build predictive models. Universities have responded quickly. Degrees in data science, analytics and artificial intelligence have expanded rapidly, and many computer science courses now include data-focused pathways. And yet, despite the volume of graduates entering the market, employers across the UK consistently report the same problem: Many data science candidates are not job-ready. Vacancies remain open. Hiring processes drag on. Candidates with impressive academic backgrounds fail interviews or struggle once hired. The issue is not intelligence or effort. It is a persistent skills gap between university education and real-world data science roles. This article explores that gap in depth: what universities teach well, what they often miss, why the gap exists, what employers actually want, and how jobseekers can bridge the divide to build successful careers in data science.

🍪 We use cookies to enhance your browsing experience on our website. By continuing to use this site, you consent to the use of cookies as described in our Cookie Policy. You can review our Cookie Policy for more information.