Senior Data Engineer

<p><b><span>Who We Are</span></b></p><p><span>At Kyndryl, we design, build, manage and modernize the mission-critical technology systems that the world depends on every day. So why work at Kyndryl? We are always moving forward – always pushing ourselves to go further in our efforts to build a more equitable, inclusive world for our employees, our customers and our communities.</span></p><p><br/><b><span>The Role</span></b></p><p><b><span><span>We’re</span><span> looking for exceptional talent to join our AI Agentic Innovation Hub at Kyndryl! </span></span><span> </span></b></p><p><span> </span></p><p><span><span>The AI Agentic Innovation Hub stands as Kyndryl’s center of excellence for advanced and agentic artificial intelligence. Our mission is to lead the design and deployment of transformative AI solutions that bridge frontier research with real-world impact — scalable, secure, and driven by measurable value.</span></span><span><span> </span></span><br/><span><span>Built upon a team of exceptional talent and </span><span>cutting-edge</span><span> technology, the Hub embodies a spirit of bold innovation and disciplined execution — an elite unit within one of the world’s leading technology companies. With national reach and global ambition, we partner with major organizations to tackle their most complex challenges, pioneering the next generation of intelligent, autonomous, and trusted systems that redefine what AI can achieve.</span></span><span> </span></p><p><b><span><span>Job Description</span></span><span> </span></b></p><p><span><span>As a Senior Data Engineer at Kyndryl’s AI Innovation Hub, you will architect, build, and </span><span>optimize</span><span> large-scale data platforms that power advanced analytics and AI-driven solutions. </span><span>You’ll</span><span> </span><span>be responsible for</span><span> designing robust data pipelines, ensuring data quality, and enabling seamless integration across cloud and on-premises environments. Working closely with data scientists, architects, and business stakeholders, you will transform complex data requirements into scalable, governed, and actionable data assets that drive enterprise innovation.</span></span><span> </span></p><p><b><span><span>Your Mission</span></span><span> </span></b></p><ul><li><p><span><span>Design, implement, and </span><span>optimize</span><span> ETL/ELT pipelines and data models for structured and unstructured data at scale.</span></span><span> </span></p></li></ul><ul><li><p><span><span>Build and </span><span>maintain</span><span> scalable data architectures supporting batch and real-time processing across cloud (AWS, Azure, GCP) and hybrid environments.</span></span><span> </span></p></li></ul><ul><li><p><span><span>Ensure data quality, lineage, and governance through robust validation frameworks and policies.</span></span><span> </span></p></li></ul><ul><li><p><span><span>Develop and </span><span>maintain</span><span> APIs and integrations for data access, supporting AI and analytics use cases.</span></span><span> </span></p></li></ul><ul><li><p><span><span>Collaborate with cross-functional teams to deliver data solutions aligned with business and AI needs.</span></span><span> </span></p></li></ul><ul><li><p><span><span>Mentor junior engineers and champion best practices in </span><span>DataOps</span><span>, CI/CD, and pipeline orchestration.</span></span><span> </span></p></li></ul><ul><li><p><span><span>Evaluate and integrate emerging data technologies, tools, and frameworks to enhance platform capabilities.</span></span><span> </span></p></li></ul><p><br/><b><span>Who You Are</span></b></p><p><b><span><span>Essential Qualifications</span></span><span> </span></b></p><ul><li><p><span><span>4</span><span>+ years of experience building and </span><span>maintaining</span><span> large-scale data warehouses and data pipelines in enterprise environments.</span></span><span> </span></p></li></ul><ul><li><p><span><span>Strong programming skills in Python and SQL, with hands-on experience in ETL/ELT tools (e.g., Airflow, </span><span>dbt</span><span>, Databricks, Kafka).</span></span><span> </span></p></li></ul><ul><li><p><span><span>Expertise</span><span> in data modeling, distributed systems, and cloud-native data services (AWS, Azure, GCP).</span></span><span> </span></p></li></ul><ul><li><p><span><span>Experience with BI tools such as Looker or </span><span>PowerBI</span><span> for data visualization and reporting.</span></span><span> </span></p></li></ul><ul><li><p><span><span>Knowledge of data governance, lineage, and observability tools.</span></span><span> </span></p></li></ul><ul><li><p><span><span>Experience with data pipeline tooling (Databricks, Cloudera, Teradata, Snowflake).</span></span><span> </span></p></li></ul><ul><li><p><span><span>Familiarity with DevOps/</span><span>DataOps</span><span> practices and CI/CD pipelines for data workflows.</span></span><span> </span></p></li></ul><ul><li><p><span><span>Fluent