Senior Lead Data Engineer

🕒 May 19

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Kyndryl

WebsiteLinkedInAll Job Openings

10,000+ employees

Founded 2021

🏢 Enterprise

🔒 Cybersecurity

☁️ SaaS

Enterprise • Cybersecurity • SaaS

Kyndryl is a leading IT infrastructure services provider, serving thousands of enterprise customers worldwide. The company specializes in designing, building, managing, and modernizing complex, mission-critical information systems. Kyndryl offers a range of services including IT consulting, cloud services, cybersecurity, data and AI solutions, and digital workplace transformation. With a strong focus on innovation, partnerships, and co-creation, Kyndryl helps businesses tackle IT complexity and drive operational excellence. The company operates across various industries such as automotive, healthcare, banking, and more, providing expertise and solutions to address industry-specific challenges. Kyndryl's global network and strategic alliances empower enterprises to adapt to the evolving technology landscape, ensuring their essential systems are reliable and efficient.

📋 Description

• Lead the integration of multiple strategic platforms, ensuring seamless data flow and interoperability to support the development of workforce optimization models. • Design, build, and maintain robust data pipelines and ETL processes that collect, cleanse, and process data from various sources to create a comprehensive data ecosystem. • Collaborate with data scientists, analysts, and other stakeholders to support build and refine optimization models that predict skills gaps and recommend actions such as upskilling, hiring, or engagement of workers. • Develop scalable data architecture solutions that ensure high performance, reliability, and accessibility of workforce data across the organization. • Work closely with cross-functional teams including HR, business units, and IT to align data engineering efforts with business needs and strategic goals. • Implement automation in data processes to improve efficiency and accuracy, continuously exploring new tools and technologies to enhance data integration and modeling capabilities. • Establish data governance practices and ensure data quality, integrity, and security are maintained across all platforms.

🎯 Requirements

• 5–8+ years of relevant data engineering experience • Strong experience in building and maintaining ETL/ELT data pipelines • Proficiency in Python and SQL for data processing • Hands-on experience with data integration across multiple enterprise platforms • Solid understanding of data architecture and data modeling • Experience with cloud platforms (AWS/Azure/GCP) and modern data tools • Knowledge of data governance, quality, and security practices • Ability to work with large, complex, and diverse datasets • Experience collaborating with data scientists, analysts, and business stakeholders • Strong problem-solving and business translation skills

🏖️ Benefits

• Flexible work arrangements • Professional development opportunities • Be Well programs to support financial, mental, physical, and social health