Advanced Business Intelligence Analyst at Diebold Nixdorf

Hyderabad, Telangana, India -

Full Time

Start Date

Immediate

Expiry Date

24 May, 26

Salary

0.0

Posted On

23 Feb, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Microsoft Fabric, Power BI, DAX, Azure Data Services, AI/ML Models, LLM-Powered Insights, Lakehouse, Warehouse, SQL, Python, Git, CI/CD, Data Governance, Dimensional Modeling, Synapse, Data Factory

Industry

IT Services and IT Consulting

Description

Key Responsibilities Design and deliver intelligent analytics solutions using Microsoft Fabric, Power BI, and Azure data services. Build and optimize semantic models (Power BI / Fabric) using advanced DAX and performance best practices. Develop AI‑enabled analytics, including: AI/ML models for forecasting, classification, or anomaly detection Agent‑based analytics (Copilot, LLM‑powered insights, conversational BI, automation agents) Work with Fabric Lakehouse, Warehouse, One Lake, and Data Pipelines for end‑to‑end analytics solutions. Collaborate with data engineering teams on ETL/ELT design, data quality, lineage, and performance tuning. Leverage Azure services (Synapse, Data Factory, Azure SQL, ADLS, ML services) where applicable. Develop reusable Python‑based data processing and ML workflows. Support CI/CD and DevOps for BI & analytics (Git, deployment pipelines, workspace promotion). Partner with business stakeholders to define KPIs, advanced metrics, and AI‑driven insights. Ensure data governance, security, and compliance across analytics solutions. Mentor junior team members and promote modern analytics best practices. Required Technical Skills Analytics & BI Power BI (advanced DAX, semantic models, performance optimization, RLS) Microsoft Fabric (One Lake, Lakehouse, Warehouse, Dataflows Gen2, Pipelines) Tabular Editor, DAX Studio Data Engineering & Cloud Azure data ecosystem (Synapse, Azure SQL, ADLS, Data Factory) Strong SQL (query optimization, indexing, stored procedures) Data modeling: Star schema, dimensional modeling, Data Vault concepts AI / ML & Automation Python for data processing and ML (pandas, scikit‑learn, or equivalent) Experience with AI/ML models and analytics use cases Exposure to AI agents, Copilot, or LLM‑based solutions (preferred) Understanding of ML lifecycle and model deployment concepts DevOps & Engineering Practices Git version control CI/CD for BI and analytics deployments Monitoring and performance tuning 5 10 Years Experience Nice to Have Banking or Retail analytics domain experience Experience migrating legacy BI solutions to Fabric Exposure to responsible AI and data governance frameworks Why should you join Diebold Nixdorf? Brightest minds + technology and innovation + business transformation The people of Diebold Nixdorf are 23,000+ teammates of diverse talents and expertise in more than 130 countries, harnessing future technologies to deliver personalized, secure consumer experiences that connect people to commerce. Our culture is fueled by our values of collaboration, decisiveness, urgency, willingness to change, and accountability. –Diebold Nixdorf is an equal opportunity employer and we value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, gender identity, age, marital status, veteran status, or disability status. ** To all recruitment agencies: Diebold Nixdorf does not accept agency resumes. Please do not forward resumes to our jobs alias, Diebold Nixdorf employees or any other organization location. Diebold Nixdorf is not responsible for any fees related to unsolicited resumes** We are a global Company operating in multiple Locations and Entities. As we are keen to find the best solution for our candidates several legal entities might be applicable for a Job offer. A List of our operating entities can be found here - https://www.dieboldnixdorf.com/en-us/about-us/global-locations

Responsibilities

The role involves designing and delivering intelligent analytics solutions using Microsoft Fabric, Power BI, and Azure data services, including building advanced semantic models and developing AI-enabled analytics like forecasting and conversational BI. Responsibilities also include collaborating on ETL/ELT design, supporting CI/CD, defining KPIs with stakeholders, and mentoring junior team members.