This role leads the development of scalable data pipelines and observability frameworks across public cloud environments (AWS, Azure, GCP) while managing and mentoring a high‑performing engineering team. The leader will drive enterprise‑grade, platform‑agnostic services, champion AI integration, automate development and operational workflows, and ensure high availability, resiliency, and performance through robust telemetry and observability solutions.
Responsibilities
- Lead and drive the development of scalable data pipelines and observability frameworks in public cloud environments (AWS, Azure, GCP).
- Manage and mentor a high-performing engineering team, ensuring delivery, team performance, quality, and on-time releases.
- Lead development of enterprise-grade services that are platform agnostic and scalable to handle high volumes of data.
- Champion the adoption and integration of AI technologies—including Agentic AI, LLMs, and modern AI tools—into engineering workflows and product development.
- Drive extensive automation for process efficiencies across development, deployment, and operational workflows.
- Implement and optimize robust services for telemetry and observability for high availability, resiliency, and performance.
- Monitor, analyze, and optimize system performance; proactively troubleshoot and resolve issues related to data flows and telemetry.
- Collaborate closely with Product, Support, Operations, and Engineering teams to deliver enhanced reliability, user experience, and operational transparency.
- Evaluate and adopt new technologies, driving continuous improvement in pipeline scalability, observability, cloud integration, and AI-powered innovation.
Requirements
- Bachelor’s or Master’s degree in Computer Science, Engineering, or related disciplines.
- 10+ years of relevant industry experience, including 2+ years in management roles.
- Demonstrated proficiency with AI technologies, including leveraging AI to drive innovation and efficiency.
- Strong programming skills (Java, Python/Go) and experience building distributed systems.
- Proven experience in product development and ownership of core platforms or user-facing features.
- Working experience with Docker, Kubernetes on cloud and on-premises.
- Ownership, accountability, and creativity in a dynamic, impact-driven engineering environment.
Nice to have
- Experience designing and scaling observability frameworks or telemetry pipelines.
- Practical experience integrating with tools/frameworks such as OpenTelemetry, Prometheus, Grafana, Datadog, Splunk.
- Excellent communication, teamwork, and leadership skills.
- Proven problem-solving skills, initiative, and a proactive engineering mindset.
Benefits
- People‑first culture that emphasizes well‑being and professional growth.
- Flexible work model allowing employees to decide how, when, and where they work.
- Strong commitment to Diversity, Equity, Inclusion, and anti‑racist initiatives.
- Inclusive environment that celebrates diverse identities and backgrounds.
Additional details
- Teradata’s Autonomous Knowledge Platform unifies data, knowledge and business context to activate enterprise intelligence.
- The team values innovation, continuous learning, open communication, mutual respect, and empowerment of team members.
- Culture emphasizes ownership, accountability, creativity, and collaborative impact‑driven engineering.
- Teradata is an equal opportunity and affirmative action employer, non‑discriminatory on the basis of protected characteristics.
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