Senior Associate Data Engineering (Azure/Databricks) Hybrid
Senior Associate Data Engineer at Publicis Sapient (Toronto, hybrid) leading delivery of large-scale data platforms, batch/streaming pipelines, and AI-enabled data foundations for client digital transformation projects. Core stack: Azure, Databricks, Spark/PySpark, Python, Scala, Airflow, plus MLOps and AI/agent data support.
- Compensation
- CA$115K–CA$160K / yr
- Location
- Toronto, Canada
- Work setup
- Not specified
- Seniority
- Senior
- Employment
- Contract
- Experience
- Not specified
- Category
- Data engineering
- Posted
Skills
Must have
- Demonstrable experience implementing end-to-end data pipelines and production-grade data platforms
- Hands-on experience with at least one leading public cloud data platform (AWS, Azure, or GCP)
- Hands-on experience with Azure Cloud Services including ADLS, Azure Functions, AKS, and Azure Databricks
- Strong Python proficiency and experience with Python-based tooling for data engineering, automation, platform development, or AI workflows
- In-depth knowledge of Scala, Apache Spark, PySpark, Python, Java, and shell scripting
- Implementation experience with column-oriented (BigQuery, Redshift, Vertica), NoSQL (DynamoDB, Bigtable, Cosmos DB), and traditional (SQL Server, Oracle, MySQL) databases
- Experience implementing streaming and batch pipelines using tools such as Glue ETL, Lambda, Cloud Dataflow, Azure Data Factory, Spark, or Spark Streaming
- Proficiency using Apache Airflow to orchestrate complex data workflows
- Experience with data modeling, warehouse design, fact/dimension implementations, and lakehouse or data mesh patterns
- Experience with code repositories, CI, automated testing, release management, and production support
- Familiarity with MLOps concepts and data engineering responsibilities for AI/ML deployment, validation, monitoring, and reliability
- Ability to handle module or track-level responsibilities while contributing hands-on
- Good communication skills and willingness to work in a collaborative, cross-functional team
- Experience mentoring, supporting, and growing junior team members
Nice to have
- Databricks as a data engineering platform: notebooks, jobs, Delta Lake, or similar lakehouse patterns
- Exposure to AI engineering patterns: context engineering, RAG support, agent architectures, production data services for AI
- Experience building pipelines behind retrieval systems: document parsing, chunking, embeddings, vector/graph databases, semantic search
- Exposure to agentic platforms or cloud AI services such as Vertex AI, Azure AI services, or AWS AI services
- Practical experience deploying agents or supporting agentic workflows in production or near-production environments
- Experience building evaluation data infrastructure for AI systems (golden datasets, offline evaluation, LLM-as-judge, regression testing)
- Experience modeling and persisting agent state: session context, conversation history, memory stores
- Experience with agentic harnesses or orchestration tools such as Pi or Hermes Agent
- Experience with Snowflake and zero-copy architecture patterns, particularly for retail, financial services, energy, or CPG use cases
- Developer certifications for AWS, Google Cloud, Microsoft Azure, Databricks, Snowflake, or related cloud/data platforms
- Demonstrated experience applying AI engineering concepts in practical business environments
- Hands-on experience supporting AI/ML and LLM lifecycle needs: model deployment support, monitoring, validation, shadow deployments, evaluation
- Experience in retail, financial services, energy, CPG, logistics, manufacturing, or other data-rich industries
Full description
Company description
Publicis Sapient is a digital transformation partner helping established organizations get to their future, digitally enabled state, both in the way they work and the way they serve their customers. We help unlock value through a start-up mindset and modern methods, fusing strategy, consulting, and customer experience with agile engineering and problem-solving creativity. United by our core values and our purpose of helping people thrive in the brave pursuit of next, our 20,000+ people in 53 offices around the world combine experience across technology, data sciences, consulting, and customer obsession to accelerate our clients’ businesses through designing the products and services their customers truly value.
Overview
Senior Associate, Data Engineering
Publicis Sapient is looking for a Senior Associate Data Engineer to be part of our team of top-notch technologists. You will lead and deliver technical solutions for large-scale digital transformation projects. Working with the latest data and AI engineering technologies in the industry, you will be instrumental in helping our clients evolve for a more digital and AI-enabled future.
Your Impact:
- Combine your technical expertise and problem-solving passion to work closely with clients, turning complex ideas into end-to-end data solutions that transform our clients’ business.
- Translate client requirements into system design and develop solutions that deliver measurable business value.
- Lead, design, develop and deliver large-scale data systems, data processing, data transformation, and data platform modernization initiatives.
- Build and optimize batch and streaming data pipelines across modern cloud data platforms and distributed processing frameworks.
- Support AI-enabled engineering use cases by designing high-quality data foundations, retrieval patterns, context engineering approaches, and scalable data services that power agentic and machine learning solutions.
- Automate data platform operations and manage post-production systems, observability, quality, reliability, and operational processes, including telemetry pipelines that capture prompt, response, trace, latency, token, and cost data for AI-enabled services in a query able form.
- Conduct technical feasibility assessments and provide project estimates for the design and development of solutions.
- Mentor, support, and grow junior team members while contributing hands-on to delivery.
Qualifications
Your Skills and Experience:
- Demonstrable experience implementing end-to-end data pipelines and production-grade data platforms.
- Hands-on experience with at least one leading public cloud data platform: Amazon Web Services, Microsoft Azure, or Google Cloud Platform;