Data & Analytics Data Engineer Professional Multiple Cities

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.

In this role, you’ll work in one of our IBM Consulting FutureNow Centers , where we deliver deep technical and industry expertise to a wide range of public and private sector clients around the world. Our delivery centers offer our clients locally based skills and technical expertise to drive innovation and adoption of new technology.

Your role and responsibilities

As a Data Engineer specializing in Google’s data platforms, you will design, build, and maintain data engineering solutions on Google’s Cloud ecosystem. You will utilize various Google services to develop batch and real‑time data pipelines, perform data migration, and design data layers.

• Design Data Pipelines: Design and build data engineering solutions using Google services such as DataProc, DataFlow, PubSub, BigQuery, BigTable, Cloud Spanner, CloudSQL, and AlloyDB for batch and real‑time data processing.
• Develop Data Migration: Develop and manage batch and real‑time data pipelines for Data Warehouse and Datalake, ensuring efficient data migration and integration.
• Manage Data Platform: Schedule and manage the data platform using Google Cloud Scheduler and Cloud Composer (Airflow), ensuring seamless data workflow and pipeline management.
• Implement Data Solutions: Implement data engineering solutions using Google Cloud Storage, BigTable, BigQuery, DataProc with Spark and Hadoop, Google DataFlow with Apache Beam or Python, and other open‑source technologies.
• Optimize Data Pipelines: Optimize and maintain data pipelines for efficiency, scalability, and reliability, ensuring high‑quality data output.

Required education

Bachelor's Degree

Required technical and professional expertise

• Strong fundamentals in data engineering, including data modeling, ETL/ELT design patterns, best practices, and data pipeline performance tuning and optimization.
• Knowledge of data governance and security principles.
• Advanced SQL skills with a focus on query performance and optimization.
• Solid Python programming skills for data processing, automation, and scripting.
• Familiarity with distributed data processing frameworks such as Spark, Beam, Flink, or similar technologies.
• Good understanding of DevOps and data quality practices, including CI/CD for data workflows, version control, and testing frameworks for pipelines and transformations.
• Familiarity with AI‑assisted development tools such as Gemini or similar technologies that support code generation, refactoring, or workflow automation.
• Advanced spoken English (B2 Level).

Preferred technical and professional experience

• Experience working with cloud platforms for data engineering (for example, AWS, GCP, or Azure).

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.

Other relevant job details

All our positions are eligible for people with disabilities PwD or rehabilitated.