Senior Lead, Data Engineering

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5 hours ago

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Kyndryl

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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.

10,000+ employees

Founded 2021

🏢 Enterprise

🔒 Cybersecurity

☁️ SaaS

📋 Description

• Platform Integration: Lead the integration of multiple strategic platforms, ensuring seamless data flow and interoperability to support the development of workforce optimization models. • Data Pipeline Development: 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. • Optimization Model: 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. • Data Management and Architecture: Develop scalable data architecture solutions that ensure high performance, reliability, and accessibility of workforce data across the organization. • Collaboration and Stakeholder Management: Work closely with cross-functional teams including HR, business units, and IT to align data engineering efforts with business needs and strategic goals. • Automation and Continuous Improvement: Implement automation in data processes to improve efficiency and accuracy, continuously exploring new tools and technologies to enhance data integration and modeling capabilities. • Data Governance and Quality: Establish data governance practices and ensure data quality, integrity, and security are maintained across all platforms.

🎯 Requirements

• Expertise in data mining, data storage and Extract-Transform-Load (ETL) processes • Experience of minimum 6 years in data pipelines development and tooling, e.g., Glue, Databricks, Synapse, or Dataproc • Experience with both relational and NoSQL databases, PostgreSQL, DB2, MongoDB • Excellent problem-solving, analytical, and critical thinking skills • Ability to manage multiple projects simultaneously, while maintaining a high level of attention to detail • Communication Skills: Must be able to communicate with both technical and non-technical colleagues, to derive technical requirements from business needs and problems

🏖️ Benefits

• Health insurance • 401(k) matching • Flexible work hours • Paid time off • Professional development opportunities