WHO YOU’LL WORK WITH

You will partner with globally distributed engineering, product, and program teams to ensure that the ecosystem of services remains loosely coupled, independently scalable, and aligned with business needs. You will work with your peers to develop key innovation features and report to the Director for your capability area.

WHO WE ARE LOOKING FOR

We are looking for a dynamic engineering manager with a passion for building and leading high-performing software engineering teams in an AI-augmented development environment. You thrive in a fast-paced, collaborative setting and have a proven track record of delivering scalable data platforms, analytics experiences, and AI-assisted engineering workflows.

Skillset Required

• 10+ years of experience in software development, with a strong foundation in distributed systems, cloud-native architectures, and data platforms.

• 3+ years of experience leading engineering teams, with demonstrated success in hiring, mentoring, and growing talent.

• 2+ years of experience driving outcomes with BI engineers and analysts, building modern analytics experiences using web-based stacks (React, Tailwind CSS, D3.js / Recharts / Observable Plot, or similar JS charting libraries) as well as governed semantic models and data marts.

• Experience establishing AI-assisted development practices across teams — including effective use of tools like Cursor, Claude Code, GitHub Copilot, and agentic coding workflows to accelerate delivery and raise code quality.

• Expertise in at least one major cloud platform: AWS, Azure, GCP, or OCI.

• Hands-on experience with Databricks, Snowflake, AWS RDS, Azure SQL, or GCP Cloud SQL, Apache Spark, and Apache Airflow.

• Strong understanding of data pipeline frameworks, metadata management, and data governance controls.Strong understanding of business-facing data consumption patterns (marketing, paid/owned channels, attribution, customer journeys).

• Experience translating data engineering outputs into interactive, self-service analytics applications. Ability to align DE + BI roadmaps to ensure last-mile delivery is not a bottleneck.

• Good to have exposure to data science workflows (feature engineering, model pipelines, experimentation frameworks) and familiarity with ML platform integration (MLflow, feature stores, model serving pipelines).

• Strong understanding of architectural design patterns and core computer science principles.Proven ability to deliver high-impact, scalable services.

• Excellent communication and stakeholder management skills.

WHAT YOU’LL WORK ON

Lead a team of software engineers responsible for building and maintaining scalable data platforms, analytics applications, and AI-augmented engineering workflows.

Drive the development of SDKs, APIs, and microservices that support enterprise-wide data, analytics, and GenAI needs.

Champion AI-assisted development practices — establish team norms for prompt engineering, agentic coding tools, AI code review, and human-in-the-loop quality gates that maximize velocity without compromising reliability.

Guide the transition from legacy BI tooling to modern, code-first analytics built on web technologies (React, TypeScript, JS visualization libraries), enabling faster iteration and richer interactivity than traditional dashboarding platforms.

Collaborate with product managers, architects, and other engineering leaders to define and execute the technical roadmap.

Foster a culture of continuous improvement, innovation, and engineering excellence — including measuring and improving how the team leverages GenAI to reduce toil and focus on high-judgment work.

Ensure the team follows best practices in software development, data governance, and platform observability.

Align engineering initiatives with broader organizational goals such as modernization, cloud cost optimization, data governance, and responsible AI adoption.