AI/ML Data Engineer (Wealth & Financial Services)

AI/ML Data Engineer (Wealth & Financial Services background) Toronto 4 days on site F2F might be required Contract Role Overview We are seeking an experienced AIML Data Engineer with a strong background in Wealth Management and Financial Services space The successful candidate will design and build modern cloudbased data platforms AIML solutions and scalable data pipelines supporting wealth analytics investment reporting client intelligence and enterprise data initiatives The role requires deep handson expertise in Data Engineering Machine Learning GenAI cloud platforms and largescale data processing within regulated financial environments Must Have Skills 8 years of Data Engineering experience including experience within Wealth Management or Financial Institutions Strong expertise with Snowflake Databricks Apache Spark PySpark and modern cloud data platforms Advanced Python development for data pipelines AIML solutions automation and API integrations Experience building scalable ETLELT frameworks using dbt DataStage SQL and cloudnative technologies Handson experience with AWS services including S3 Lambda SNS IAM and cloud data architectures Experience with Kafka Kinesis Snowpipe REST APIs and realtime data ingestion frameworks Deep SQL expertise including performance tuning data modeling warehousing and analytics engineering Experience developing ML models for forecasting customer analytics attrition prediction or financial analytics Knowledge of GenAI RAG architectures Vector Databases LangChain LLM integration and document intelligence solutions Experience with Airflow Autosys CICD pipelines Terraform Kubernetes Docker and MLOps practices Strong understanding of data governance data quality security compliance and financial reporting requirements Excellent stakeholder management and ability to work with business technology and data leadership teams Good to Have Skills Experience working with Wealth Management platforms investment products portfolio analytics and market data Exposure to Elasticsearch FAISS Snowpark Redshift Aurora and DB2 Experience converting legacy SASDataStage workloads into Spark or cloudnative architectures Knowledge of Power BI QuickSight Tableau or enterprise reporting platforms Experience implementing enterprise GenAI and AI governance frameworks MBA or advanced degree in Business Data Science Engineering or related field AWS andor cloud certifications Key Responsibilities Design and implement enterprisescale data platforms supporting Wealth Build and optimize data ingestion transformation and analytics pipelines processing highvolume financial data Develop AIML and GenAI solutions that improve client insights operational efficiency and decision support Implement robust data quality observability monitoring and governance controls Support cloud modernization migration and architecture initiatives Collaborate with business stakeholders and technology teams to translate requirements into scalable solutions Lead technical design discussions and provide mentorship to junior engineers

Design and implement enterprise-scale data platforms and scalable pipelines to support wealth analytics and investment reporting. Develop AI/ML and GenAI solutions to improve client insights and operational efficiency within a regulated financial environment.

Requires at least 8 years of data engineering experience specifically within wealth management or financial institutions. Must possess deep expertise in cloud platforms (AWS), big data tools (Spark, Snowflake), and modern AI/ML frameworks including GenAI and RAG.

• KubernetesSouhaitée
• SQLSouhaitée
• Apprentissage automatiqueSouhaitée
• Amazon Web ServicesSouhaitée
• TerraformSouhaitée
• PythonSouhaitée

Relevées dans la description du poste. Confirmez les exigences importantes ci-dessus.

• Snowflake
• Databricks
• Apache Spark
• PySpark
• Python
• dbt
• AWS
• Kafka
• SQL
• Machine Learning
• GenAI
• RAG Architectures
• Airflow
• Terraform
• Kubernetes
• MLOps

• Data & Analytics
• Technology
• Finance & Accounting
• Engineering
• Consulting

Formation minimale

Maîtrise

Expérience minimale

10+ ans

Postuler avant le

20 sept. 2026

Langue de l’offre

anglais

Heures de travail

40 heures par semaine

Présence au bureau

4 jours par semaine

Niveau d’expérience

Mid-Senior level

Mode de candidature

La candidature directe est offerte