Engineering Manager - Data Platform

Two Circles•Vancouver, BC

About The Position

We are seeking an Engineering Manager to lead our Measurement Data Engineering team within the Partnership Intelligence Platform. This is an exciting opportunity for a people-focused engineering leader who is passionate about building high-performing teams, improving engineering execution, and helping talented data engineers do their best work. The Measurement team plays a critical role in delivering scalable, reliable, and high-quality data capabilities that power our platform and support the evolving needs of our customers. As Engineering Manager, you will be responsible for the health, effectiveness, and growth of the team. You will provide line management for multiple data engineers, create an environment of accountability and continuous improvement, and partner closely with Engineering Leadership, Product, QA, Support, Client Enablement, and other stakeholders to deliver meaningful outcomes. This role is ideal for someone who brings a strong engineering background, understands modern data platforms, and is ready to lead through people, process, and execution. You will help shape how the team plans, delivers, communicates, and grows. The team consists of mostly experienced senior-level data-engineers in both Vancouver and Hyderabad. It is expected that this role will mostly focus on engineering management with opportunities in hands-on development. About The Role As an Engineering Manager, you will lead a team of data engineers responsible for building and evolving data products, pipelines, services, and platform capabilities. While this is not primarily a hands-on individual contributor role, your technical judgment and understanding of data engineering will be essential in guiding the team, supporting decision-making, and ensuring strong engineering standards. You will be accountable for team performance, delivery effectiveness, career development, engineering practices, and day-to-day team operations. You will work closely with the Engineering Director to align team priorities with broader engineering strategy, while partnering with Product Management and other stakeholders to ensure the team is focused on the highest-value work. In this role, you will be expected to: Lead, coach, and support a team of data engineers through regular 1:1s, performance conversations, feedback, and career development planning. Drive team effectiveness across regions by improving ways of working, delivery processes, collaboration patterns, and engineering practices. Partner with Product, QA, Engineering Leadership, Support, and Client Enablement to align priorities, clarify expectations, and ensure successful delivery. Foster a culture of ownership, accountability, technical excellence, collaboration, and continuous learning. Support the growth of the India-based engineering hub by contributing to hiring, onboarding, and team development.

Requirements

6+ years of experience in software engineering, data engineering, or a closely related technical field.
2+ years of experience managing, coaching, or formally leading engineers.
Experience leading engineering teams in a fast-paced, agile product environment.
Strong understanding of modern data engineering concepts, including data pipelines, data quality, orchestration, batch processing, cloud infrastructure, and production operations.
Experience working with cross-functional stakeholders such as Product Management, QA, Support, Client Enablement, Engineering Directors, and business teams.
Experience supporting performance management, goal setting, career development, feedback conversations, and team planning.
Experience improving engineering processes, delivery predictability, team collaboration, and operational maturity.
Experience participating in hiring, onboarding, and growing engineering teams.
Data pipelines, ingestion patterns, data quality, reliability, and scalability.
Cloud infrastructure and services, preferably AWS.
Orchestration and batch processing technologies such as Apache Airflow.
Data platforms and databases such as Snowflake and MS SQL Server.
Python-based data engineering environments. Familiarity with C# and .NET is a plus.
CI/CD, automated testing, monitoring, documentation, and production support practices.
Containerization technologies such as Docker.
API-based integrations and distributed systems.
Monitoring and observability tools such as New Relic or similar platforms.
Differences between batch-oriented and streaming-oriented data integrations.
Strong people leadership skills with the ability to coach, motivate, and develop engineers at different career stages.
Proven ability to create clarity, alignment, and accountability within a team.
Strong performance management skills, including giving direct feedback, recognizing strong performance, and addressing growth areas constructively.
Ability to partner effectively with technical leads and senior engineers without needing to own every technical decision.
Strong stakeholder management skills with the ability to communicate priorities, risks, trade-offs, and progress clearly.
Ability to improve team execution through practical process improvements, lightweight structure, and continuous feedback.
Strong organizational and prioritization skills, with the ability to manage multiple initiatives and competing demands.
Comfortable working with distributed or global teams, primarily in Vancouver, London and Hyderabad.
Familiarity with Lean-Agile methodologies such as Scrum or Kanban.
Excellent written and verbal communication skills.
People-first and outcomes-driven — invested in helping engineers grow while ensuring the team delivers meaningful business value.
Curious and technically grounded — able to engage in technical discussions, ask strong questions, and support sound decision-making.
Operationally thoughtful — motivated to improve how the team plans, builds, releases, supports, and learns.
Collaborative and transparent — able to build trust with engineers, peers, leadership, and stakeholders.
Accountable and proactive — willing to take ownership of team health, delivery, communication, and continuous improvement.
Growth-oriented — always looking for ways to improve the team, the platform, the process, and themselves.
Calm in complexity — comfortable leading through ambiguity, competing priorities, and evolving business needs.

Nice To Haves

Familiarity with C# and .NET is a plus.

Responsibilities

Manage multiple data engineers, providing line management, coaching, feedback, and performance support.
Build and maintain a high-performing engineering team by setting clear expectations, creating development plans, and supporting individual career growth.
Own goal setting, performance planning, and regular performance conversations for team members.
Partner with the Engineering Director to translate engineering strategy into actionable team goals and priorities.
Work closely with Product Management to understand roadmap priorities, clarify scope, and support predictable delivery.
Collaborate with QA to improve quality practices, test coverage, release confidence, and defect prevention.
Partner with Support and Client Enablement to understand customer-impacting issues, improve operational responsiveness, and strengthen feedback loops.
Improve team effectiveness through better planning, estimation, delivery tracking, retrospectives, and continuous improvement practices.
Advocate for engineering best practices including design reviews, code quality, CI/CD, monitoring, documentation, automation, and production ownership.
Help the team balance delivery commitments with technical debt reduction, platform reliability, maintainability, and long-term scalability.
Support engineers in making sound technical decisions, escalating risks, and collaborating effectively with architects, leads, and senior engineers.
Create an inclusive and transparent team environment where engineers feel supported, challenged, and empowered.
Participate in recruiting, interviewing, onboarding, and ramping new data engineering team members.
Identify opportunities to improve developer experience, team workflows, internal tooling, and engineering processes.
Promote strong communication across global teams and ensure stakeholders have visibility into progress, risks, and trade-offs.