AI Data Engineer

Join our global Centre of Excellence as a subject matter expert (SME) for Agentic AI Services, collaborating with teams worldwide to drive innovation and excellence. As part of this central function, you will help shape, implement, and scale cutting-edge Agentic AI solutions across the organization and our clients. RequirementsBachelor’s degree or equivalent in Computer Science, Software Engineering, Information Technology, or a related quantitative/engineering field. Minimum 5-10 years of experience designing, building, and optimizing modern data solutions in Microsoft Azure, especially with Microsoft Fabric, Data Factory, and Synapse. Relevant Microsoft certifications (e.g., Azure Data Engineer Associate, Microsoft Certified: Fabric Analytics Engineer) are highly regarded. Deep expertise in data pipeline creation, transformation, and automation using Microsoft Fabric, Azure Data Factory, Power Query, Synapse Analytics, and Microsoft SQL-based solutions. Excellent understanding of modern data engineering practices, including data lakehouse architectures, ETL/ELT design, and data modeling in the context of preparing data for AI systems. Strong grasp of both logical and physical data modeling concepts, with experience implementing schemas that optimize data utilization by analytics and AI platforms. Analytical mindset with robust problem-solving abilities, capable of translating business requirements into scalable data engineering solutions. Demonstrated programming skills in SQL, Python, PowerShell, and (where relevant) Dataflow/Spark languages within the Microsoft data engineering ecosystem. Familiarity with data governance, lineage, and quality assurance practices in Microsoft Purview and related Microsoft tools. Expertise with multiple database types, including Azure SQL, Fabric Lakehouse, Azure Data Lake, and third-party sources (SAP, Oracle, etc.). Experience with real-time and batch data processing, scaling data pipelines to support high-volume/complex analytics requirements. Skilled in mentoring and guiding less experienced team members to adopt best-in-class cloud data engineering and tools. Demonstrated experience in ingesting, transforming, and structuring data from large and complex, multi-terabyte data sources for analytics and AI/ML applications. Proven success in automating and scripting data pipelines (Python, PowerShell, SQL, etc.) for scalable, repeatable ingestion and transformation both on-premises and in cloud. Experience with various database and data warehouse platforms (Azure SQL, Fabric Lakehouse, SAP, Oracle, etc.) and integrating, migrating, and validating data across applications. Familiarity with big data tools (Hadoop, Spark) as integrated within the Microsoft Azure ecosystem is preferred. Experience with end-user tools such as Power BI and Excel (pivots, macros) and supporting quality assurance for downstream reporting and analytics. Track record of supporting enterprise migration to AI-driven analytics solutions and mentoring teams in adopting modern Microsoft data engineering practices. Excellent command of both spoken and written English. BenefitsNew beginnings can be a challenge. We promise a smooth integration and a supportive mentorPick your working style: choose from Remote, Hybrid or Office work opportunitiesEarly bird or night owl? Our projects have different working hours to suit your needsNobody is born an expert. Sharpen your tech skills with our sponsored certifications, trainings and top e-learning platformsWe want you to stay healthy! Enjoy our Private Health Insurance ⁠– it’s custom-made for youA clear mind is a healthy mind. Attend individual coaching sessions or go one step further by joining our accredited Coaching SchoolMake the most of our epic parties or themed events – they’re lovingly designed for our people and their familiesOriginally posted on Himalayas Apply To this Job