Lead Service Data Engineer

Overview

Lead Service Data Engineer responsible for building, scaling, and operationalizing data platforms that support service reliability, operational visibility, and data-driven technology operations.

What you'll do

• Implement operational data architecture through production-grade pipelines and canonical schemas.
• Build and operate batch and streaming pipelines from ITSM, observability, cloud, CI/CD, and infrastructure systems.
• Implement data contracts, validation, testing, lineage, and dataset SLA/SLO controls.
• Build curated datasets, semantic layers, and metrics for dashboards, analytics, and automation.
• Establish coding standards, CI/CD practices, design reviews, and reference implementations.
• Collaborate with architecture, SRE, IT Ops, Security, and Analytics stakeholders.
• Implement RBAC/ABAC, retention, encryption, and auditability controls.

What you'll need

• 10+ years of experience as a Data Engineer working with complex, large-scale data.
• Bachelor's degree in Computer Science, Information Technology, or a related field.
• Strong SQL and Python skills.
• Experience designing and delivering production-grade batch and streaming pipelines.
• Experience building data products and applying security governance principles.
• Familiarity with ITSM, observability, cloud data sources, and data quality practices.
• Strong problem-solving, communication, and project-management skills.

Nice to have

• Experience with AIOps, correlation, or anomaly detection.
• Familiarity with data-platform SLA/SLO enforcement frameworks.
• Experience with capacity planning, cost, and reliability engineering data.
• Experience shaping canonical schemas and data models with architecture teams.
• Experience with Jenkins, CodePipeline, CloudFormation, Terraform, or Ansible.

Details

• Hybrid work model with 2–3 days per week in the office, depending on the role.
• Work from anywhere for up to 8 weeks per year.