**Introduction** As a Data Engineer, you will play a key role in designing, building, and optimizing data pipelines and processing solutions that enable data-driven decision-making across the organization. Leveraging expertise in SQL, Spark, and Python, alongside AWS data integration and processing technologies (Glue, Athena, Redshift), you will ensure that our data infrastructure is scalable, secure, and high performing. You will work closely with data analysts, data scientists, and business stakeholders to deliver reliable, well-tested, and high-quality data solutions. You will contribute to modernizing data architectures, implementing performance optimizations, and supporting the adoption of lakehouse design principles. In this role, you'll work in one of our IBM Consulting Client Innovation Centers (Delivery 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** What will you do? * Design, develop, and maintain scalable data pipelines for ingestion, transformation, and loading. * Implement AWS-based data integration and processing solutions using tools such as Glue, Athena, and Redshift. * Write clean, efficient, and maintainable code using SQL, Spark, and Python. * Conduct functional and automated testing of data pipelines to ensure accuracy, reliability, and performance. * Perform performance tuning, optimization, and debugging of data workflows. * Collaborate with cross-functional teams to understand data requirements and translate them into technical solutions. * Contribute to the design and development of lakehouse architectures. * Ensure best practices for data governance, quality, and security are followed. * Maintain technical documentation, including data flow diagrams, pipeline specifications, and troubleshooting guides. **Required technical and professional expertise** Experience: * Minimum 5+ years of experience in data engineering or related technical roles. * Proven experience in developing and maintaining large-scale data pipelines. * Hands-on experience with AWS data services (Glue, Athena, Redshift). Technical Skills: * Strong knowledge of SQL, Spark, and Python. * Proficiency in data analysis and transformation workflows. * Experience with functional and automated testing of data pipelines. * Understanding of performance tuning and debugging for data processes. * Some knowledge of lakehouse architecture and design principles. * Familiarity with cloud security best practices and compliance requirements. Soft Skills: * Strong problem-solving and analytical abilities. * Excellent communication skills for working with technical and non-technical stakeholders. * Ability to work collaboratively in cross-functional teams. * Attention to detail and commitment to delivering high-quality solutions. * Strong organizational skills with the ability to manage multiple priorities. IBM is committed to creating a diverse environment and 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, caste, genetics, pregnancy, disability, neurodivergence, age, veteran status, or other characteristics. IBM is also committed to compliance with all fair employment practices regarding citizenship and immigration status.