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Added 1 hour ago
Indirect Tax Manager - Canada
Stellantis Financial Services US
Toronto, ON
Full-time
Knowledge of tax automation solutions such as Avalara, Vertex, SAP Tax, OneSource, or similar platforms.
Added 4 hours ago
Proposal Coordinator
Vertex Resource Group
Sherwood Park, AB
With these two words, Vertex makes the promise that we will always be versatile in developing solutions to our clients’ unique needs and that we will always demonstrate expertise in our…
Added 9 hours ago
Technology Lead
Infosys
ON
Integrate Gen AI solutions with cloud-native services (AWS Bedrock, Azure OpenAI, GCP Vertex AI).
Added 11 hours ago
AI Outcome Customer Developer, Forward Deployed Development
Google
Toronto, ON
As an AI Outcome Customer Developer in our GTM AI Tech organization, you work as an enterprise architect, technical debugger, development liaison and technical delivery manager. You will…
Added 15 hours ago
Machine Learning Scientist
DarkVision
North Vancouver, BC
Full-time
Hands-on experience with ML lifecycle management tools like MLFlow, Amazon SageMaker, GPC Vertex AI, etc.
Added 19 hours ago
AI Full Stack Development Lead
Accenture
Toronto, ON
Full-time
Develop and deploy applications on Google Cloud Platform (GCP) using cloud-native design principles including Vertex AI, Gemini API, and Cloud Run.
Added 21 hours ago
Senior Associate Data Engineering (Azure/Databricks) Hybrid
Publicis Sapient
Toronto, ON
Full-time
Exposure to agentic platforms or cloud AI services such as Vertex AI, Azure AI services, AWS AI services, or comparable platforms; specific platform experience is less important than…
Added 1 day ago
Architecte de solutions / Lead technique IA
Onepoint
Montreal, QC
Full-time
Expérience des plateformes infonuagiques (AWS, Azure, GCP) et des services IA infonuagiques (SageMaker, Azure Machine Learning, Vertex AI, Bedrock);
Added 1 day ago
Senior Manager - Program & Project Management
LTM
ON · Ontario, Canada
$81,215 to $133,000 USD / year
Full-time
Proven experience working with cloud based AI platforms Azure ML or AWS SageMaker or GCP Vertex AI
Added 1 day ago
Credit Risk Manager
Pwc Canada
Toronto, ON
Full-time
Experience and exposure to AI/ML modeling, including theoretical approach and related technology and platforms (such as Vertex AI, Azure AI, etc. ) would be an asset
Added 1 day ago
Credit Risk Manager
PwC Canada
Toronto, ON
Full-time
Experience and exposure to AI/ML modeling, including theoretical approach and related technology and platforms (such as Vertex AI, Azure AI, etc. ) would be an asset
Added 1 day ago
AI DevOps Specialist (AI Enablement & Secure DevOps)
Celestica International LP
Toronto, ON
…foundational AI cloud services (primarily Google Cloud Platform - Vertex AI), managing user-facing web interfaces (LibreChat or Gemini Enterprise Agent Platform), implementing agentic…
Added 1 day ago
Marketing Associate Director, CF
Vertex Pharmaceuticals
Toronto, ON
Full-time
Vertex is seeking an experienced marketing professional to join our Canadian team to lead our Cystic Fibrosis (CF) Marketing team. The Associate Marketing Director, CF Marketing will be a…
Added 2 days ago
Marketing Associate Director, CF
Vertex Inc.
Toronto, ON
Full-time
Vertex is seeking an experienced marketing professional to join our Canadian team to lead our Cystic Fibrosis (CF) Marketing team. The Associate Marketing Director, CF Marketing will be a…
Added 2 days ago
Generative AI Cloud Operations Engineer - Evinova
Evinova
Mississauga, ON
Full-time
Leverage Vertex AI, Azure Foundry, OpenAI, Anthropic, and other foundation model platforms to provide reliable and stable access to LLMs
Added 2 days ago
Manager, Customer Care - Support Team
Jobgether
Canada
Full-time
Hands-on experience with systems such as Genesys, CIS, and Vertex.
Added 2 days ago
Manager, Customer Care - Support Team
Jobgether
Canada
Full-time
Hands-on experience with systems such as Genesys, CIS, and Vertex.
Added 2 days ago
Generative AI Cloud Operations Engineer - Evinova
AstraZeneca
Mississauga, ON · Canada - Mississauga
Full-time
Leverage Vertex AI, Azure Foundry, OpenAI, Anthropic, and other foundation model platforms to provide reliable and stable access to LLMs
Added 5 days ago
Sr. Data Scientist
Charger Logistics Inc
Brampton, ON
Full-time
Operate MLOps workflows on Google Cloud using Vertex AI Pipelines, Feature Store, and Model Registry, supporting model training, deployment, monitoring, and drift detection.
Added 4 days ago
Applied AI Engineer
Hygiena
Mississauga, ON
Full-time
…Enterprise, tool use, extended thinking, Claude Code; Gemini API, Vertex AI Agent Builder, grounding; OpenAI Assistants/Responses APIs, Agents…
Added 5 days ago
Sr. Data Scientist
Charger Logistics Inc.
Brampton, ON
Full-time
Operate MLOps workflows on Google Cloud using Vertex AI Pipelines, Feature Store, and Model Registry, supporting model training, deployment, monitoring, and drift detection.
Added 5 days ago
Technology Lead - GenAI Lead
Infosys
Mississauga, ON
Full-time
Integrate Gen AI solutions with cloud-native services (AWS Bedrock, Azure OpenAI, GCP Vertex AI).
Added 5 days ago
Technology Lead - GenAI Lead
Infosys
Mississauga, ON
Full-time
Integrate Gen AI solutions with cloud-native services (AWS Bedrock, Azure OpenAI, GCP Vertex AI).
Added 5 days ago
Technology Lead - GenAI Lead
Infosys
Mississauga, ON
Full-time
Integrate Gen AI solutions with cloud-native services (AWS Bedrock, Azure OpenAI, GCP Vertex AI).
Added 5 days ago
Technology Lead - GenAI Lead
Infosys
Mississauga, ON
Full-time
Integrate Gen AI solutions with cloud-native services (AWS Bedrock, Azure OpenAI, GCP Vertex AI).

Publicis Sapient

Senior Associate Data Engineering (Azure/Databricks) Hybrid

Toronto, ON, Canada

Pay: Salary Range: $115,000 - $160,000
Job type: Full-time
Apply by: Oct 22, 2026
Posting language: English
Posted: Sep 22, 2026

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Original job description

Job Description

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;
Hands-on experience with Azure Cloud Services, including Azure Data Lake Storage (ADLS), Azure Functions, Azure Kubernetes Service (AKS), and Azure Databricks.
Experience with Databricks as a data engineering platform is strongly preferred, including working with notebooks, jobs, Delta Lake, or similar lakehouse patterns.
Strong Python proficiency and practical experience using Python-based tooling for data engineering, automation, platform development, or AI engineering workflows.
In-depth knowledge of Scala, Apache Spark, PySpark, Python, Java, and shell scripting.
Implementation experience with column-oriented database technologies such as BigQuery, Redshift, Vertica, or similar platforms; NoSQL database technologies such as DynamoDB, Bigtable, Cosmos DB, or similar; and traditional database systems such as SQL Server, Oracle, or MySQL.
Experience implementing data pipelines for both streaming and batch integrations using tools and frameworks such as Glue ETL, Lambda, Google Cloud Dataflow, Azure Data Factory, Spark, Spark Streaming, or similar technologies.
Proficiency using Apache Airflow to orchestrate complex data workflows.
Experience with data modeling, warehouse design, fact/dimension implementations, and modern lakehouse or data mesh patterns.
Experience with code repositories, continuous integration, automated testing, release management, and production support practices.
Familiarity with MLOps concepts and the data engineering responsibilities required to support AI/ML deployment, validation, monitoring, rollback, and operational reliability.
Ability to handle module or track-level responsibilities while contributing to tasks hands-on.
Good communication skills and willingness to work as part of a collaborative, cross-functional team.

AI Engineering & Modern Data Platform Experience:

Exposure to AI engineering patterns, including context engineering, retrieval-augmented generation support patterns, agent architectures, and production data services that support AI-enabled experiences.
Experience building and maintaining the pipelines behind retrieval systems, including document parsing, chunking, metadata extraction, embedding generation, and incremental reindexing, alongside the vector databases, graph databases, semantic search, and knowledge retrieval structures they feed.
Exposure to agentic platforms or cloud AI services such as Vertex AI, Azure AI services, AWS AI services, or comparable platforms; specific platform experience is less important than understanding how AI engineering differs from traditional data engineering.
Practical experience deploying agents, integrating agent frameworks, or supporting agentic workflows in production or near-production environments is a plus.
Experience building evaluation data infrastructure for AI systems, including ground-truth and golden datasets, offline evaluation pipelines, and the data scaffolding behind LLM-as-judge and regression testing.
Experience modeling and persisting agent state, including session context, conversation history, and memory stores, treating them as a durable storage and data modeling problem rather than an application detail.
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, applying the same lineage, provenance, and data contract rigor to context and retrieval sources that you would to a production warehouse.
Experience with agentic harnesses or orchestration tools such as Pi, Hermes Agent, or similar platforms is a plus, but not required.
Experience with Snowflake and zero-copy architecture patterns is a plus, particularly for retail, financial services, energy, or CPG-oriented use cases.

Set Yourself Apart With:

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 rather than only academic or research settings.
Hands-on experience supporting AI/ML and LLM lifecycle needs such as model deployment support, monitoring, validation, shadow deployments, release management, and evaluation or data quality measurement for both predictive models and generative systems.
Experience in retail, financial services, energy, CPG, logistics, manufacturing, or other data-rich industries where applied AI and large-scale data engineering are used to solve operational or client-facing problems.
Good understanding of capital markets domain requirements, particularly FINRA compliance.
Understanding of Agile, product, and delivery methodologies in consulting or client-facing environments.

Additional Information

Salary Range: $115,000 - $160,000

The range shown represents a grouping of relevant ranges currently in use at Publicis Sapient. Actual range for this position may differ, depending on location and specific skillset required for the work.

An inclusive workplace that promotes diversity and collaboration.
Access to ongoing learning and development opportunities.
Competitive compensation and benefits package.
Flexibility to support work-life balance.
Comprehensive health benefits for you and your family.
Generous paid leave and holidays.
Wellness program and employee assistance.

As part of our dedication to an inclusive and diverse workforce, Publicis Sapient is committed to Equal Employment Opportunity without regard for race, color, national origin, ethnicity, gender, protected veteran status, disability, sexual orientation, gender identity, or religion. We are also committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures. If you need assistance or an accommodation due to a disability, you may contact us at hiring@publicis.sapient.com

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.

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More about this job

Responsibilities

You will lead and deliver large-scale data systems, data processing, and platform modernization initiatives for digital transformation projects. Additionally, you will design high-quality data foundations and retrieval patterns to support AI-enabled engineering use cases.

Requirements

Candidates must have demonstrable experience implementing end-to-end data pipelines and production-grade data platforms on public cloud services like Azure. Proficiency in Python, Spark, and modern data engineering frameworks is required, along with experience in AI engineering patterns.

Skills

Azure
Databricks
Python
Spark
Data engineering
Cloud platforms
Data pipelines
AI engineering
Delta Lake
Kubernetes
SQL
NoSQL
Apache Airflow
Data modeling
MLOps
Retrieval-augmented generation

Benefits

Health benefits
Paid leave
Holidays
Wellness program
Employee assistance
Learning and development opportunities

Visa sponsorship

Not detected in the job text

Keywords

Azure
Databricks
Python
Spark
Delta Lake
Kubernetes
Data Engineering
AI Engineering
Cloud Computing
Data Pipelines
NoSQL
SQL
Apache Airflow
MLOps
Retrieval-Augmented Generation
Data Modeling
Data Mesh
BigQuery
Redshift
Cosmos DB
Vertex AI
Agile
Consulting
Digital Transformation
Telemetry
Vector Databases
LLM
Data Warehouse
Automation
Distributed Systems

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