Engineering Manager, Data Engineering

About Wunderkind:

Wunderkind is a performance marketing solution that uses AI and data to help brands acquire and retain customers through one-to-one, personalized messages across websites, email, text, and ads, guaranteeing a lift in revenue. Founded in 2010, Our goal is to scale a brand’s ability to create and grow customer relationships through websites, email, text, and ads. We believe individuals should have the freedom to choose the kind of internet they want. An internet that fosters genuine relationships with brands. An internet that treats humans like real people instead of “web traffic.” We also believe in empowering brands to treat their customers as individuals, satisfying their unique needs with tailored experiences and thoughtful communication. By expertly personalizing, automating, and scaling beautiful one-to-one experiences, Wunderkind helps brands acquire new customers at scale and keep them loyal for life.

What You’ll Do 

• Run a team of talented data and backend engineers while building robust & scalable services to be used company wide 
• Drive the vision, strategy, and execution of Wunderkind’s data platform team across both Wunderkind’s marketing and advertising business verticals — including: 
• Promotions: how we incentivise someone to purchase 
• Compliance: from auditory compliance to contractual compliance 
• Data collection: covering both data pipelines, the real time event stream including the capturing of real time conversion data 
• Data Governance and DataLake Services: how we scale and understand our data from the engineering POV 
• Collaborate with internal stakeholders to gather requirements for new data use cases and ensure alignment with business objectives. 
• Partner closely with product to deliver scalable, safe, and high-performance data systems.
• Work with analytics to ensure data quality, availability, and reliability. 
• Lead internal discovery with both technical and non-technical users to understand data needs and use cases. 
• Monitor performance metrics and KPIs to ensure services are robust, efficient, and delivering value. 
• Champion best practices around repository health, on call practices, and code reviews.
• Identify and mitigate risks around data loss, privacy violations, or compliance issues (e.g., GDPR, CCPA, Data Acquisition Attacks). 
• In partnership with Product define KPIs, monitor product performance, and continuously prioritize roadmap based on impact, scalability, and stakeholder feedback. 
• Evangelize the importance of high-quality data practices across the organization.
• Educate and enable cross-functional teams (including Product Support and Professional Services) on data platform services capabilities, value proposition, and features. 

Required Qualifications

• 2-3 years of experience in engineering management, ideally with at least 2 years experience building on data platform, data infrastructure and/or data collection systems. 
• Strong technical understandings covering data streaming technology (e.g. Google Pub/Sub, Kafka, RedPanda), data pipeline tools (e.g. Airflow, Composer), data streaming languages (e.g. Python, Spark, Scala), backend languages (e.g. GoLang, Java), and databases (e.g. relational databases, non relational databases, and open table format data structures) 
• Deep understanding of APIs, message streaming, and high availability systems
• Excitement to work on data privacy and compliance frameworks. 
• Demonstrated success leading cross-functional initiatives with engineering and data teams
• Comfortable balancing technical complexity with user and business value. 
• Excellent communication, collaboration, and project management skills. 

Who You Are 

• Highly organized and detail-oriented, but not afraid to push boundaries or question assumptions.
• A self-starter with a passion for building innovative products in a fast-paced, data-driven environment.
• Energized by providing customer value 
• Constantly curious about how better to set the team up for success

The base salary range for this role is CAD 105,000 to CAD 155,000. Actual compensation packages are based on several factors that are unique to each specific candidate; including but not limited to skill set, depth of experience, applicable certifications, and geographic work location. This may vary depending on living location and market rate.

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