Engineering Manager (AI and Data platform)

100% Remote

The Data Platform Engineering Manager will lead the Platform Management Team at Financial, ensuring the scalability, reliability, and security of our Databricks and AWS-based data ecosystem. This role requires expertise in platform engineering, Site Reliability Engineering (SRE), DevOps, DataOps, and cloud infrastructure to support the organization s data-driven decision-making and analytics capabilities .
Duties & Responsibilities:
Designing Solutions

• Guide technical solution design and architecture for the data platform.
• Review and provide direction on system architecture, scalability, and security .
• Collaborate with engineers to drive best practices in platform design and operations .

Developing Software & Platform Engineering

• Stay hands-on with code reviews , ensuring adherence to best engineering practices .
• Ensure platform observability and reliability with monitoring, logging, and alerting .
• Lead the automation of infrastructure, CI/CD pipelines, and deployments.

Learning & Applying New Techniques

• Promote innovation by fostering continuous learning and technical excellence .
• Stay ahead of emerging trends in data platforms, DevOps, and DataOps .

Collaborating within the Team

• Support Agile practices , sprint planning, and retrospectives.
• Work closely with Product Managers to align platform capabilities with business needs.
• Foster a culture of collaboration, psychological safety, and innovation within the team.

Collaborating Across Teams & Organization

• Work cross-functionally with Data Engineering, Data Science, and Infrastructure teams .
• Advocate for standardized platform practices across multiple product teams.
• Align the platform roadmap with strategic goals and technology vision .

Setting Product/Platform Technology Strategy

• Define and execute the technical roadmap for Databricks and AWS platforms.
• Influence decisions on technology upgrades, cloud cost optimization (FinOps), and automation .
• Ensure the platform supports business intelligence, AI/ML, and data governance requirements .

Defining Engineering Standards & DevOps/DataOps

• Champion engineering best practices , including DevOps, DataOps, observability, and incident management .
• Define SLAs, SLOs, and error budgets to improve reliability and uptime.
• Optimize Databricks performance, AWS infrastructure, and automation pipelines .
• Implement DataOps best practices to enhance data pipeline reliability, quality, and governance.

Selecting & Managing Technology Vendors

• Guide build vs. buy decisions for data platform technologies.
• Manage vendor relationships for Databricks, AWS services, and observability tools .

Coaching Engineers & Building Talent

• Mentor and coach engineers , supporting career growth and technical development.
• Recruit and develop high-performing platform engineers to sustain growth.
• Foster a culture of accountability, continuous improvement, and technical excellence .

Qualifications & Skills:
Required:

• 8+ years of experience in data platform engineering, cloud infrastructure, or SRE .
• 3+ years of leadership experience managing engineering teams.
• Deep expertise in Databricks, AWS, Kubernetes/OpenShift, Terraform, CI/CD automation, DevOps, and DataOps .
• Strong background in cloud cost optimization (FinOps), security, and compliance .
• Experience working in Agile environments , driving cross-team collaboration .

Preferred:

• Financial services or fintech industry experience.
• Experience with Snowflake, Kafka, Airflow, dbt, Apache Iceberg, and DataOps automation .
• MBA or relevant leadership certifications.

This role is critical to ensuring data platform operates efficiently, securely, and at scale. It provides the technical leadership necessary to support digital transformation and data-driven strategy .