Director, Data Engineering & Product Data

Indigo is a physical and digital place inspired by and filled with books, ideas, beautifully designed lifestyle products, and the creative people who help make it all happen. We believe in real books, living life fully and generously, being kind to each other and to the environment, and that stories — big and little — connect us. Indigo is our customer's happy place — for joyful moments of discovery and to connect with people who share their passion for reading, their belief in ideas, and their commitment to making the world a better and more beautiful place. OUR GUIDING PRINCIPLES Our Mission is to inspire reading and enrich the lives of booklovers. As such, we believe in the power of people and their stories. We aim to attract top talent, nurture the potential of our employees, and create space for everyone to thrive. Our Guiding Principles are the few key ideas that are meant to influence everything we do, every day. We Will Hire, Inspire, Promote and Retain the Best – A’s Hire A’s We Will Be Customer Centric We Will Be Data Driven – System Thinking – Entrepreneurial We are Committed to True and Shared Value Creation We Will Be Human-Centered and AI Enabled We are Committed to Caring About Each Other, Our Communities, Our Environment MISSION The Director, Data Engineering & Product Data is a senior technology leader accountable for three connected disciplines: enterprise data engineering, master data, and product data development. They own a stable, governed, and secure end-to-end pipeline from Digital and Enterprise into Snowflake; modernize how master data is curated and corrected so the business can scale across a 10M+ SKU catalogue; and deliver fault-tolerant, cost-efficient vendor data ingestion and processing. The Director provides the engineered data foundations powering analytics, phygital experiences, reporting, and 1:1 customer personalization across Indigo. KEY PERFORMANCE METRICS Pipeline reliability and SLA adherence — uptime, latency, and data freshness targets for all critical data flows Data quality — accuracy, completeness, and consistency scores across product information, customer data, and transactional data Personalization enablement — timely delivery of data products supporting data science models, segmentation, and 1:1 personalization On-time, on-budget, on-scope delivery of engineering initiatives against the roadmap Platform cost efficiency — Snowflake and infrastructure spend relative to usage, with continuous optimization Team growth, engagement, and ongoing improvement of data engineering practices KEY ACCOUNTABILITIES Functional Architect, build, and maintain scalable batch and real-time data pipelines that extract, transform, and load data from SAP (ERP, EWM, BW) and other key Digital/Enterprise systems into Snowflake as the data lake platform Lead the migration of legacy SAP BW workloads into Snowflake on a defined decommissioning timeline, retiring duplicated reporting paths and improving run-time, stability, and total cost of ownership Define and maintain data architecture, modelling standards, governance, and lineage practices to ensure data assets are consistent, compliant, and trustworthy across the platform Own the end-to-end process for inbound vendor product data ingestion, re-architecting pipelines for fault tolerance, scalability and continuous cost reduction Oversee Product Information Management strategy and operations — including taxonomy design, product attributes, metadata standards, and content quality — ensuring data readiness across all channels Modernize the master data operating model to enable scaled, self-serve correction Provide the engineered data foundations — including curated datasets, feature stores, event streams, and identity resolution — that support the development and deployment of data science models for customer personalization Establish and enforce data governance frameworks, including data quality monitoring, lineage documentation, access controls, and compliance with privacy regulations Develop and execute the multi-year data engineering roadmap in alignment with Indigo's technology and business strategy Proactively monitor pipeline health and infrastructure performance, leading rapid incident diagnosis and resolution to minimize business impact Optimize Indigo's cloud data platform, including storage patterns, lifecycle policies, and cost management to support analytics, reporting, and ML workloads Continuously improve data engineering processes by automating manual workflows, reducing technical debt, and evaluating new tools and technologies that enhance team productivity and platform capability Ensure the completion of team deliverables and set/adhere to team budgets, as applicable Act as an advocate for the customer by placing them at the forefront of all design and decision-making processes Proactively identify and anticipate customer expectations and needs Embrace and seek out technology that creates high tech and high touch solutions for Indigo's customers Challenge the status quo and consistently identify areas for improvement, diagnose issues and work to resolve them People Build, lead, and develop a high-performing cross-functional team spanning data engineering, development, and product information disciplines Collaborate with others to drive flexible and iterative solutions, quickly and easily Share technical knowledge with others and actively seek to learn from those more knowledgeable than yourself Help others see the impacts of their efforts and proactively engage other functions to get input Encourage others to freely share their point of view and be open to feedback Cultural Model Indigo’s beliefs and convey a positive image in everything you do Celebrate diversity of thought and have an open mindset Take an active role in fostering a culture of continual learning, taking risks without the fear of making mistakes Embrace, champion and influence change through your team and/or the organization KEY RELATIONSHIPS Internal: CTO / Technology Leadership Team Personalisation teams Digital and Enterprise technology teams Digital Merchandising and Marketing Finance, Planning and Supply Chain Operations External: Platform vendors Implementation and consulting partners Work Experience / Education / Certifications Bachelor's degree in Computer Science, Software Engineering, Information Systems, or a related field; equivalent practical experience considered 8+ years of progressive experience in data engineering, data platform development, or related technical disciplines, with 3+ years in a people leadership role Demonstrated expertise building and operating enterprise-scale data pipelines on modern cloud data platforms; hands-on Snowflake required, with working knowledge of Azure and GCP/BigQuery; experience in an agile delivery environment required; retail or e-commerce background strongly preferred Proven experience leading MDM and/or PIM at scale, including stewardship operating models, data quality remediation, and self-serve correction workflows for business users Cloud certification (e.g., Microsoft Certified: Azure Data Engineer Associate, Google Professional Data Engineer, or Snowflake SnowPro Core) is an asset Competencies / Skills / Attributes Deep expertise in Snowflake architecture and ETL/ELT pipeline design, with working knowledge of BigQuery; hands-on experience with Apache Airflow and/or Azure Data Factory; strong SQL and Python skills; comfort using AI-assisted engineering tools (e.g. Cursor) to accelerate pipeline development Experience extracting and transforming data from SAP modules (ERP, EWM, BW), including familiarity with IDocs, BAPIs, RFC/BAPI connectors, and CDS Views Solid understanding of data modelling (dimensional, star schema, data vault), data quality frameworks, and observability practices Familiarity with data science workflows and the ability to partner effectively with data scientists on feature engineering, model deployment, and experimentation infrastructure Strong understanding of data governance, security, privacy (PIPEDA), and compliance best practices; experience with Git and CI/CD practices for data pipeline development Strong communicator who can translate complex data and technical concepts for non-technical stakeholders; able to lead and hold a team accountable for quality, delivery, and continuous improvement Indigo uses artificial intelligence (AI) tools to assist with certain aspects of the hiring process, such as screening and assessments. These tools support our team but do not replace human judgment. We are committed to using AI responsibly, fairly, and in compliance with applicable employment and anti-discrimination laws. We regularly review these tools to help prevent bias or discrimination. At Indigo, Diversity, Equity, Inclusion, and Accessibility are core to our values. We integrate these principles into our training, policies, and hiring practices and continuously evolve to reflect the needs of the communities we serve. We welcome applicants from all backgrounds and lived experiences, including but not limited to individuals who identify as BIPOC (Black, Indigenous, and People of Colour), members of the 2SLGBTQIA+ community, and persons with disabilities. If you require an accommodation during the recruitment process, please contact Human Resources at [email protected]. We respect your privacy throughout the recruitment process. Our Candidate Privacy Notice explains how we collect, use, and protect your personal information when you apply for a role with Indigo, and the choices available to you. This posting is for a current opportunity within Indigo.