The OpportunityThis position is for a Team Lead, Data Engineering with deep expertise in cloud data architecture, data modeling, SQL, and data governance for enterprise-level systems.Responsibilities and DutiesDesign, develop, and maintain enterprise data architecture strategies, standards, and blueprints that support operational, analytical, and AI/ML workloads.Architect cloud-native data solutions across AWS (Redshift, RDS, Glue, Lake Formation) or equivalent platforms, ensuring scalability, security, and cost efficiency.Define and enforce data modeling standards, including dimensional modeling, denormalized schemas, OLTP/OLAP design patterns, and AI-friendly ontologies.Architect and oversee data transformation layers using DBT, ensuring modular, tested, and well-documented models across the analytics and reporting stack.Lead the design of data integration and orchestration patterns using Prefect and Airflow, including batch ETL, real-time streaming, event-driven architectures, and API-based data exchange.Define and implement data validation, quality control, and testing frameworks to ensure accuracy, completeness, and consistency of data across pipelines and warehouses.Establish data quality SLAs, monitoring, and alerting standards; design automated checksand reconciliation processes to catch issues before they impact downstream consumers.Establish and maintain data governance frameworks covering data quality, lineage, cataloging, classification, and access control.Collaborate with Data Engineers, Software Engineers, Product,



and Analytics teams to translate business requirements into scalable, maintainable data designs.Evaluate and recommend data technologies, tools, and platforms; own the technicaldecision-making for data infrastructure within assigned domains.Design data partitioning, indexing, and optimization strategies to support high-performance queries and big data workloads.Define and document data contracts, schemas, and interface specifications across services and teams.Ensure data architectures are designed to support downstream AI/ML consumption, including feature stores, embedding pipelines, and model training datasets where applicable.Perform architecture reviews and code reviews to ensure adherence to data standards, optimal execution patterns, and long-term maintainability.Validate and cleanse data and handle error conditions gracefully.Mentor data engineers on best practices in data modeling, architecture patterns, and cloud data design.Assist with automated release management and CI/CD processes as they relate to data infrastructure and pipeline deployments.RequirementsExperience managing and mentoring a team is required - proven experience managing, mentoring, and developing team members.7+ years of experience in data architecture, data engineering,



or related technical roles.5+ years of experience designing and implementing cloud-based data architectures (AWS, GCP, or Azure).5+ years writing complex SQL queries with RDBMSes.5+ years of experience with developing and deploying ETL/ELT pipelines using Airflow, Prefect, or similar tools.Strong experience with DBT for data transformation, testing, and documentation.Experience with data warehouse design: OLTP, OLAP, star schemas, snowflake schemas, dimensions, and facts.Experience with data modeling tools and methodologies (conceptual, logical, physical models).Experience with cloud-based data warehouses such as Redshift, Snowflake, or BigQuery.Experience implementing data validation frameworks, quality control processes, and automated testing for data pipelines.Familiarity with how data architectures serve AI/ML workloads, including feature stores and vector-based retrieval patterns.Robust understanding of data governance, data quality frameworks, and metadata management.Experience with cloud-based data architectures, messaging, and analytics.Bachelor's degree in Computer Science or equivalent - preferredPluses - Experience withPython development, including Pandas and PySparkDockerAWS Lambdas/Step FunctionsDatabricksVector databases (Pinecone, Weaviate, pgvector)Data mesh or data fabric architectural patternsGraph databases or knowledge graph designCloud certificationsThe annual compensation range for this role is $135,000 – $145,000 CAD#J-18808-Ljbffr

📌 Team Lead, Data Engineering - C$135,000 - C$145,000 A Year (Toronto)
🏢 Haptiq
📍 Toronto