Data & Analytics Senior Data Engineer - AI & Analytics Infrastructure Professional

A career in IBM Consulting is built on long‑term client relationships and close collaboration worldwide. You’ll work with leading companies across industries, helping them shape their hybrid cloud and AI journeys. With support from our strategic partners, robust IBM technology, and Red Hat, you’ll have the tools to drive meaningful change and accelerate client impact. At IBM Consulting, curiosity fuels success.

You’ll be encouraged to challenge the norm, explore new ideas, and create innovative solutions that deliver real results. Our culture of growth and empathy focuses on your long‑term career development while valuing your unique skills and experiences.

• Design, build, and maintain robust data pipelines that ingest, transform, and deliver high‑quality data across the platform.
• Develop scalable architectures using Microsoft Fabric, Databricks, and/or Azure Synapse Analytics.
• Ensure pipelines are performant, reliable, and built to handle the scale and variability of enterprise data.
• Implement data transformation and orchestration workflows that feed AI models and analytics dashboards.
• Architect and maintain the underlying data infrastructure that supports AI and analytics use cases.
• Define and implement data lakehouse patterns, medallion architecture, and layered data models.
• Collaborate with AI engineers and architects to ensure data outputs are structured and accessible for model consumption.
• Manage and optimize data storage, compute, and processing environments for cost and performance.
• Implement data quality checks, validation frameworks, and monitoring to ensure trustworthy data outputs.
• Establish and enforce data governance standards including lineage tracking, cataloging, and access controls.
• Partner with stakeholders to document data assets and ensure discoverability across the platform.

Bachelor's Degree

Master's Degree

• 7+ years of experience designing, developing, and maintaining scalable batch and real‑time data pipelines across Azure and AWS.
• Build and optimize enterprise data platforms leveraging services such as Azure Data Factory, Azure Data Lake, AWS S3, AWS Glue, Databricks, and Snowflake.
• Develop robust ETL/ELT frameworks supporting analytics, reporting, operational, and AI/ML use cases across cloud and hybrid ecosystems.
• Implement scalable ingestion and transformation pipelines for structured, semi‑structured, and unstructured enterprise data sources.
• Support data industrialization efforts through reusable pipeline frameworks, standardized engineering practices, observability, monitoring, automated testing, and CI/CD deployment patterns.
• Enable trusted enterprise data foundations by implementing data quality controls, metadata management, lineage, cataloging, and governance capabilities.
• Optimize data models, distributed processing workloads, storage strategies, and query performance within Databricks and Snowflake environments.
• Integrate enterprise applications, APIs, ERP systems, CRM platforms, and event‑driven architectures into centralized cloud data platforms.
• Collaborate with AI engineers, architects, analysts, and business stakeholders to support analytics, AI, and generative AI initiatives.
• Support Infrastructure‑as‑Code, cloud‑native deployment practices, and secure enterprise data operations across Azure and AWS platforms.

• Familiarity with Azure Data Factory, Event Hubs, or other Azure data integration services.
• Experience implementing data governance frameworks and working with data cataloging tools.
• Knowledge of MLOps data pipelines and feature engineering for AI model consumption.
• Background supporting Agentic AI or generative AI programs where data quality is mission‑critical.

IBM is proud to be an equal‑opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, gender, gender identity or expression, sexual orientation, national origin, genetics, pregnancy, disability, neurodivergence, age, or other characteristics protected by the applicable law. IBM is also committed to compliance with all fair employment practices regarding citizenship and immigration status.