Data Technical lead

The Global Information Systems Group is dedicated to the success of Lam through providingbest-in-class and innovative information system solutions and services. Together, we supportusers globally with data, information, and systems to achieve their business objectives.

Join Lam as an IT Engineer, where you'll be at the forefront of designing, analyzing, and implementing applications and systems that form the foundation of our infrastructure. As a crucial member of our IT team, you'll contribute your technical assistance and guidance to projects for various systems and infrastructures. Acting as a technical liaison, you'll address complex business problems with automated systems solutions. Your expertise will be instrumental in driving Lam's commitment to innovation and efficiency.

The Senior Technical Lead - Data Operations is responsible for designing, operating, and continuously improving large-scale data platforms and services that support critical business and analytics workloads. This role combines deep expertise in big data technologies with strong operational leadership to ensure reliability, performance, scalability, security, and cost efficiency across the data ecosystem. The ideal candidate brings hands-on experience with Apache Spark and Azure HDInsight, strong Site Reliability Engineering (SRE) practices, and proven ability to lead teams and managed service partners supporting production-grade data operations.

Key Responsibilities:

• Lead day-to-day operations of enterprise data platforms and pipelines, ensuring SLAs for uptime, reliability, data accuracy, and processing latency are consistently met.
• Own production support and operational excellence for big data environments built on Apache Spark and Azure HDInsight.
• Define and implement SRE practices including service level objectives (SLOs), service level indicators (SLIs), error budgets, observability, alerting, incident response, problem management, and post-incident reviews, with clear alignment to uptime, data accuracy, and latency targets.
• Drive proactive monitoring, capacity planning, performance tuning, resiliency engineering, and automation for data processing platforms, with focus on preventing breaches in uptime, accuracy, and latency commitments.
• Manage and govern managed service providers and external operational partners, including work prioritization, service quality, SLA adherence, uptime, data quality, latency performance, escalation handling, and continuous improvement.
• Collaborate with data engineering, analytics, infrastructure, security, and platform teams to ensure seamless operation of batch and streaming data workloads.
• Provide technical leadership for Spark job optimization, cluster sizing, workload tuning, dependency management, and platform stability.
• Establish operational runbooks, standard operating procedures, support models, and production readiness criteria for new services and changes.
• Lead root cause analysis for production incidents, identify systemic issues, and implement corrective and preventive actions.
• Drive automation of deployment, monitoring, recovery, housekeeping, and operational tasks to reduce manual effort and improve service quality.
• Ensure platform governance, security compliance, access controls, backup/recovery readiness, and audit support across the data operations landscape.
• Mentor engineers and operational teams, promote engineering best practices, and build a culture of accountability, reliability, and continuous learning.

• Bachelor's or Master's degree in Computer Science, Information Systems, Engineering, or a related field.
• 8+ years of experience in data engineering, data platform operations, site reliability engineering, or production support for enterprise data systems.
• Strong hands-on experience with Apache Spark in production environments, including performance tuning, troubleshooting, job orchestration, and operational support.
• Experience with Azure HDInsight and related Azure services supporting data workloads.
• Strong understanding of distributed systems, cluster operations, workload management, data processing pipelines, and platform reliability.
• Practical experience implementing SRE principles such as observability, incident management, reliability engineering, automation, and service health measurement.
• Experience managing managed services teams or external vendors supporting 24x7 operations.
• Strong knowledge of monitoring and logging tools, operational dashboards, and alerting frameworks.
• Experience with scripting or programming in Python, Scala, SQL, or similar technologies for automation and data operations.
• Strong communication, stakeholder management, and technical leadership skills.
• Ability to balance operational stability with continuous improvement and delivery demands.

• Experience supporting streaming and messaging technologies such as Kafka or event-driven data architectures.
• Knowledge of cloud cost optimization, FinOps practices, and platform usage governance.
• Experience with infrastructure-as-code, CI/CD, DevOps tooling, and platform automation.
• Familiarity with data governance, security controls, and enterprise compliance requirements.
• Experience in leading technical teams across global delivery or follow-the-sun support models.
• Azure or cloud platform certifications related to data engineering, operations, or architecture.

• Stable and reliable operation of data platforms with measurable improvements in uptime, incident reduction, and recovery times.
• Well-defined operational processes, runbooks, and support models that improve consistency and reduce risk.
• Improved service observability and actionable monitoring that enables faster issue detection and resolution.
• Effective governance and performance management of managed service providers.
• Improved platform performance, cost efficiency, and scalability for growing data workloads.
• A strong operational culture focuses on ownership, prevention, automation, and continuous improvement.

We believe it is important for every person to feel valued, included, and empowered to achieve their full potential. By bringing unique individuals and viewpoints together, we achieve extraordinary results.

Lam Research ("Lam" or the "Company") is an equal opportunity employer. Lam is committed to and reaffirms support of equal opportunity in employment and non-discrimination in employment policies, practices and procedures on the basis of race, religious creed, color, national origin, ancestry, physical disability, mental disability, medical condition, genetic information, marital status, sex (including pregnancy, childbirth and related medical conditions), gender, gender identity, gender expression, age, sexual orientation, or military and veteran status or any other category protected by applicable federal, state, or local laws. It is the Company's intention to comply with all applicable laws and regulations. Company policy prohibits unlawful discrimination against applicants or employees.

Lam offers a variety of work location models based on the needs of each role. Our hybrid roles combine the benefits of on-site collaboration with colleagues and the flexibility to work remotely and fall into two categories - On-site Flex and Virtual Flex. 'On-site Flex' you'll work 3+ days per week on-site at a Lam or customer/supplier location, with the opportunity to work remotely for the balance of the week. 'Virtual Flex' you'll work 1-2 days per week on-site at a Lam or customer/supplier location, and remotely the rest of the time.

#LI-DM1