Microsoft Power BI Technical Specialist
# Microsoft Power BI Technical Specialist **HCLTech** · Hyderabad, Telangana · `On-site` 🕒 **Статус:** *Опубликовано: сегодня* · *Источник: Indeed* --- ### About the Role Microsoft Power BI Technical Specialist Hyderabad, Telangana Job Summary Data Engineer Grade: D Job Description At Lloyds Banking Group, we’re reshaping financial services for millions by putting customers first, data at the core and leading with cutting-edge technology and AI. And now, we’re looking for a brilliant mind to help lead the charge within our AI Centre of Excellence. As a Data Engineer, you’ll be a driving force behind one of the most ambitious transformations in UK financial history, transforming how insights are created and consumed across the Bank. With over 30 million customers, billions of transactions, and 70,000+ colleagues, you’ll tap into one of the richest data ecosystems in the country. And you’ll harness it through AI and Generative BI capabilities, crafting tools that make decision-making intuitive and intelligent. What you’ll be doing You’ll design and build robust, scalable data pipelines and platforms that power analytics and AI solutions across the organisation—turning raw, complex datasets into reliable, high quality data assets that drive confident decision making.‑quality data assets that drive confident decision‑making. Key responsibilities include: Design and build next gen data pipelines and platforms that power intelligent analytics, AI solutions, and scalable GenAI use cases across the Group‑gen data pipelines and platforms Collaborate across geographies to translate stakeholder needs into robust data architectures—owning everything from technical scoping to high quality delivery‑quality delivery Work hand‑in‑hand with agile teams of engineers, analysts, and data scientists to create bold, resilient, and scalable data solutions Develop and optimise data models that ensure accuracy, consistency, and performance for downstream consumption, analytics, and conversational intelligence Leverage Google Cloud, BigQuery, dbt, and modern data engineering tools to build secure, automated, cloud native data ecosystems‑native data ecosystems Engineer and orchestrate intelligent data flows that enhance relevance, quality, and reliability for generative and analytical tools Support user teams and product squads through documentation, training, and adoption activities to help scale data engineering capabilities across the Group What you bring At least 4 years of hands-on experience building and optimising data pipelines, cloud data platforms, and production grade data workflows‑grade data workflows Solid foundations in data modelling and engineering principles — think orchestration, optimisation, lineage, and scalable architecture Python skills that go beyond the basics — clean, modular code for ETL/ELT, automation, and data processing at scale Strong proficiency in SQL and modern cloud ecosystems, especially BigQuery, with experience working across distributed data environments A strong sense for data quality and governance, proactively shaping datasets that unlock value, reliability, and confident decision making‑making An ability to translate complex data engineering into clear, compelling narratives, enabling teams to understand, trust, and use data effectively Bonus points if you’ve taken data products from prototype to fully industrialised, highly‑available solutions in complex enterprise environments. We get it — Generative BI is fresh, fast-moving, and maybe not something you’ve had the chance to dive into just yet. That’s why we’re not expecting perfection. What matters most to us is your curiosity, your technical mindset, and a proactive attitude. If you're the kind of person who sees challenge as opportunity, we're ready to invest in you and help grow the Generative BI skills you'll need to thrive in this space. We’re building a team of pioneers — not just experts, but learners, innovators, and bold thinkers. If that sounds like you, we’d love to talk. This role is based in the Lloyds Technology Centre (LTC) and operates as a service provider to the UK business team (CDAO). While the activities and respon Key Responsibilities Data Engineer Grade: D Job Description At Lloyds Banking Group, we’re reshaping financial services for millions by putting customers first, data at the core and leading with cutting-edge technology and AI. And now, we’re looking for a brilliant mind to help lead the charge within our AI Centre of Excellence. As a Data Engineer, you’ll be a driving force behind one of the most ambitious transformations in UK financial history, transforming how insights are created and consumed across the Bank. With over 30 million customers, billions of transactions, and 70,000+ colleagues, you’ll tap into one of the richest data ecosystems in the country. And you’ll harness it through AI and Generative BI capabilities, crafting tools that make decision-making intuitive and intelligent. What you’ll be doing You’ll design and build robust, scalable data pipelines and platforms that power analytics and AI solutions across the organisation—turning raw, complex datasets into reliable, high quality data assets that drive confident decision making.‑quality data assets that drive confident decision‑making. Key responsibilities include: Design and build next gen data pipelines and platforms that power intelligent analytics, AI solutions, and scalable GenAI use cases across the Group‑gen data pipelines and platforms Collaborate across geographies to translate stakeholder needs into robust data architectures—owning everything from technical scoping to high quality delivery‑quality delivery Work hand‑in‑hand with agile teams of engineers, analysts, and data scientists to create bold, resilient, and scalable data solutions Develop and optimise data models that ensure accuracy, consistency, and performance for downstream consumption, analytics, and conversational intelligence Leverage Google Cloud, BigQuery, dbt, and modern data engineering tools to build secure, automated, cloud native data ecosystems‑native data ecosystems Engineer and orchestrate intelligent data flows that enhance relevance, quality, and reliability for generative and analytical tools Support user teams and product squads through documentation, training, and adoption activities to help scale data engineering capabilities across the Group What you bring At least 4 years of hands-on experience building and optimising data pipelines, cloud data platforms, and production grade data workflows‑grade data workflows Solid foundations in data modelling and engineering principles — think orchestration, optimisation, lineage, and scalable architecture Python skills that go beyond the basics — clean, modular code for ETL/ELT, automation, and data processing at scale Strong proficiency in SQL and modern cloud ecosystems, especially BigQuery, with experience working across distributed data environments A strong sense for data quality and governance, proactively shaping datasets that unlock value, reliability, and confident decision making‑making An ability to translate complex data engineering into clear, compelling narratives, enabling teams to understand, trust, and use data effectively Bonus points if you’ve taken data products from prototype to fully industrialised, highly‑available solutions in complex enterprise environments. We get it — Generative BI is fresh, fast-moving, and maybe not something you’ve had the chance to dive into just yet. That’s why we’re not expecting perfection. What matters most to us is your curiosity, your technical mindset, and a proactive attitude. If you're the kind of person who sees challenge as opportunity, we're ready to invest in you and help grow the Generative BI skills you'll need to thrive in this space. We’re building a team of pioneers — not just experts, but learners, innovators, and bold thinkers. If that sounds like you, we’d love to talk. This role is based in the Lloyds Technology Centre (LTC) and operates as a service provider to the UK business team (CDAO). While the activities and respon Skill Requirements Other Requirements
Наблюдалась 2026-09-21, впервые 2026-09-21, найдена на 3 площадках, источник — Indeed.