Company description Publicis Groupe Canada is the Canadian subsidiary of Publicis Groupe, one of the largest communications group in the world and a global leader concentrated within four main activities: Communication, Media, Data and Technology. Publicis Groupe Canada represents the vision of a set of collaborative and integrated agencies that offer expertise and insightful services to many of the biggest brands in North America. Canadian brands include: Publicis Canada (Publicis Canada, Hawkeye, Razorfish, Publicis Health, ThePubProductions, Nurun, Publicis Sports & Entertainment), Publicis Media (Starcom, Spark Foundry, Zenith), Leo Burnett (Leo Burnett Canada, Ove Brand Design, Leo Burnett Design), Saatchi & Saatchi (Saatchi & Saatchi Canada, Synergize, TPM),MSL Canada/North Strategic (North Strategic, MSL Canada, Notch Canada) and Publicis Sapient. Overview We are looking for a Senior Data Engineer to build and operate production-grade data pipelines and Lakehouse models that power a large-scale customer and marketing data ecosystem. You will help transform complex, multi-source data into trusted datasets and curated layers that support reporting, advanced analytics, and downstream data products. You will partner with product, strategy, analytics, and engineering teams to define data contracts and SLAs, implement ingestion and transformation patterns, and ensure strong data quality, lineage, governance, and observability in production. The role is hands-on in a cloud lakehouse environment and requires an ownership mindset across the lifecycle—from design and build to operations, cost/performance optimization, and secure handling of sensitive and privacy-regulated data (including data residency constraints). Responsibilities Data Pipelines & Ingestion Design, build, and operate reliable batch and streaming pipelines to onboard data from APIs, databases, event streams, and file drops into the lakehouse. Implement scalable ETL/ELT transformations (Spark/SQL) and curate data through standardized layers (e.g., bronze/silver/gold) with clear ownership and SLAs. Integrate multiple sources and implement consistent keys, business rules, and validation checks in partnership with platform and analytics teams. Build automated data quality checks, tests, and reconciliation to ensure trusted, production-grade outputs. Design for multi-environment delivery: implement strong access control patterns and secure handling of sensitive data. Data Modeling & Serving Design analytics-friendly models (dimensional and/or wide-table) and publish curated datasets for BI and self-service use cases. Build and optimize lakehouse structures to support downstream analytics applications and advanced analytics workflows. Define consistent metric logic and implement semantic modeling patterns to enable governance, reuse, and self-service analytics. Optimize performance and cost via partitioning, clustering, file sizing, and workload tuning across storage and compute. Maintain lineage and documentation so stakeholders can understand dataset meaning, freshness, and limitations. Platform, Orchestration & Operations Build and maintain orchestration workflows (e.g., ADF/Airflow) with robust retry, alerting, backfill, and dependency management. Build and maintain modeling and retraining pipelines, including automated scheduling, monitoring, and safe promotion across environments. Develop and operate in an Azure + Databricks ecosystem; implement lakehouse best practices (Delta formats, job design, cluster policies) for reliable production performance. Implement CI/CD for data pipelines and infrastructure-as-code to enable safe, repeatable releases across environments. Establish observability (logging, monitoring, data freshness/volume checks) and incident response practices; troubleshoot production issues end to end. Apply governance and security controls (RBAC, secrets management, encryption, auditability) and support catalog/permission models (e.g., Unity Catalog or equivalents). Collaboration & Client Enablement Work closely with cross-functional teams (product, engineering, analytics) to deliver end-to-end data solutions for business-critical data products. Drive alignment on data definitions, contracts, and operational expectations (SLAs/SLOs), including privacy, residency, and governance constraints. Guide technical decisions through clear documentation, trade-off discussions, and pragmatic architecture recommendations. Mentor engineers through pairing, code reviews, and best practices around testing, reliability, and operational excellence. Qualifications 6+ years of experience in data engineering (or equivalent), building and operating data pipelines and platforms in production. Strong programming skills in Python and SQL; solid software engineering practices (clean code, automated testing, code reviews, Git). Hands-on experience with distributed processing (Spark) and designing efficient transformations at scale. Strong experience building data solutions on cloud platforms—preferably Azure—with practical knowledge of IAM, networking, storage, and cost optimization. 3+ years of experience with Databricks (jobs, notebooks, workflows) and lakehouse concepts (Delta/data lakes/data warehouses) including data modeling for analytics. Proficiency with orchestration and scheduling tools (e.g., Azure Data Factory, Airflow) and CI/CD for data workloads. Strong understanding of data quality, observability, governance, and security (access control, encryption, PII handling). Comfortable working in Agile delivery environments and collaborating with client stakeholders. Nice to Have Experience working with customer/marketing data, complex entity relationships, and privacy-preserving data collaboration approaches. Experience with streaming technologies (Kafka, Event Hubs, Kinesis, Pub/Sub) and real-time processing patterns. Experience with dbt and modern analytics engineering practices (semantic layers, metric definitions) including enabling natural-language-to-SQL where applicable. Familiarity with data quality and observability tooling (e.g., Great Expectations, Monte Carlo, Datadog). Experience with containerization and orchestration (Docker, Kubernetes) and infrastructure-as-code (Terraform). Additional information Location & Eligibility: Candidates must be based in the Greater Toronto Area with valid Canadian work authorization of at least 12 months. Hybrid Work: This role follows a hybrid model with 3 days per week at our Toronto office: 111 Queen St. E, Suite 200, Toronto, ON M5C 1S2. Compensation: The salary range for this position is $110,000–$140,000 per year, based on experience, skills, and relevant certifications. We believe in pay transparency and are committed to offering competitive, market-aligned compensation. Flexibility & Global Mobility: Work remotely for up to 6 weeks per year from any of our 50+ global offices through our Work Your World program. Time Off: - Up to 3 weeks annual vacation, with additional paid closure between Christmas and New Year's - Extended long weekends for provincial holidays — we give you both the Monday and Friday so you get a full 4-day break - 6 sick days and 2 personal days per year Benefits: Comprehensive group coverage including: - Medical, dental, and vision care - Psychological and paramedical services - Disability insurance - Fertility support and gender-affirming care - Dedicated internal guidance programs for employees navigating cancer, fertility treatments, or gender transition We use artificial intelligence (AI) tools to support parts of our hiring process, such as reviewing applications or analyzing resumes. These tools assist our recruitment team but never replace human decision-making. We believe in a human-first approach, where your experience and potential are recognized by people. Publicis Canada is committed to building a diverse workforce representative of our community. We encourage and are pleased to consider all qualified candidates, without regard to race, colour, citizenship, religion, sex, marital / family status, sexual orientation, gender identity, aboriginal status, age, disability or persons who may require an accommodation, to apply. If you require a specific accommodation please contact Human Resources at 416-925-7733 or by email at inquiries@publicisna.com