Data Engineer

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.

Your Role And Responsibilities

We are looking for a skilled and motivated Data Engineer to join our team. In this role, you will design, build, and maintain scalable data pipelines and infrastructure that support analytics, reporting, and data-driven decision-making across the organization. You will work closely with data analysts, data scientists, software engineers, and business stakeholders to ensure reliable and efficient access to high-quality data.

Your Primary Responsibilities Will Include

• Design, develop, and maintain scalable ETL/ELT pipelines
• Build and optimize data models, data warehouses, and data lakes
• Integrate data from multiple internal and external sources
• Ensure data quality, consistency, and reliability across systems
• Monitor and troubleshoot pipeline and platform issues
• Improve data processing performance and cost efficiency
• Collaborate with cross-functional teams to understand data requirements
• Implement and maintain data governance, security, and compliance standards
• Document data architecture, workflows, and best practices

• Bachelor’s degree in Computer Science, Engineering, Information Systems, or related field, or equivalent practical experience
• 3–5 years of experience in data engineering or a related field
• Strong proficiency in SQL and Python
• Experience building and maintaining ETL/ELT pipelines
• Hands-on experience with cloud platforms such as AWS, GCP, or Azure
• Familiarity with data warehousing concepts and tools
• Experience with workflow orchestration tools such as Airflow or similar
• Understanding of database technologies, including relational and NoSQL databases
• Knowledge of version control and CI/CD practices
• Strong problem-solving and communication skills

• Experience with big data technologies such as Spark, Kafka, or Hadoop
• Familiarity with modern data stack tools such as dbt, Snowflake, BigQuery, or Redshift
• Experience with containerization tools such as Docker and Kubernetes
• Understanding of data governance and security best practices
• Experience supporting analytics or machine learning workloads