Data Platform Engineering Manager

Overview

Lead the strategy, delivery, and operations of the data platform capabilities that support analytics, reporting, telemetry, and data products across the business, managing a team of data platform engineers.

What you'll do

• Lead the design, delivery, and evolution of the enterprise data platform architecture.
• Manage a team of data platform engineers and coordinate work across engineering, cloud, analytics, and product stakeholders.
• Define standards for data modeling, retention, partitioning, lifecycle management, access control, and data quality.
• Oversee the development and support of event-driven data pipelines using technologies such as Kafka and cloud-native services.
• Guide the use of storage and analytics technologies including data lake, data warehouse, columnar database, and time-series storage patterns.
• Partner with teams using platforms such as AWS, Azure, or GCP to support scalable and secure data solutions.
• Improve observability, reliability, and performance across data services and operational workflows.
• Support CI/CD and Infrastructure as Code practices using tools such as Terraform and CloudFormation.
• Collaborate on telemetry, metadata, logs, and system health data that support dashboards, monitoring, and proactive operations.
• Mentor engineers and strengthen team capability through coaching, code review, design review, and knowledge sharing.

What you'll need

• 10+ years of experience in software engineering, data engineering, platform engineering, or a closely related discipline.
• Experience leading engineering teams, with responsibility for delivery, quality, and team development.
• Bachelor's degree in Computer Science, Engineering, Data Science, or a related technical field.
• Experience designing and operating cloud-native data platforms on AWS, Azure, or GCP.
• Strong knowledge of event-driven data pipelines, streaming frameworks such as Kafka, and enterprise data storage patterns.
• Hands-on understanding of data lake, data warehouse, columnar database, and time-series storage technologies.
• Experience with data governance, security, encryption, access control, and compliance in enterprise environments.
• Familiarity with DevOps practices, CI/CD integration, and Infrastructure as Code tools such as Terraform and CloudFormation.
• Strong communication skills with the ability to align technical teams and business stakeholders.

Nice to have

• Experience with telemetry, observability, or real-time data environments such as logs, metrics, system health, or event streams.
• Exposure to Prometheus, Grafana, Datadog, or ELK.
• Experience supporting ML or advanced analytics pipelines.
• Background in SaaS or multi-tenant platform design.