We are hiring for an AI/ML Data Engineer- Wealth Management and Financial Services. The role focuses on building cloud-based data platforms, scalable data pipelines, and AI/ML solutions supporting wealth analytics and financial data initiatives.

A strong fit will have 8+ years of data engineering experience with Wealth Management or Financial Services experience and strong expertise in modern data and AI technologies.

What You Bring

- 8+ years of Data Engineering experience, including experience within Wealth Management or Financial Institutions.
- Strong expertise with Snowflake, Databricks, Apache Spark, PySpark, and up-to-date cloud data platforms.
- Advanced Python development for data pipelines, AI/ML solutions, automation, and API integrations.
- Experience building scalable ETL/ELT frameworks using dbt, DataStage, SQL, and cloud-native technologies.
- Hands-on experience with AWS services including S3, Lambda, SNS, and IAM.
- Experience with Kafka, Kinesis, Snowpipe, REST APIs, and real-time data ingestion frameworks.
- Deep SQL expertise including performance tuning, data modeling, data 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, CI/CD pipelines, Terraform, Kubernetes, Docker, and MLOps practices.




- Strong understanding of data governance, data quality, security, compliance, and financial reporting requirements.
- Excellent stakeholder management skills and ability to work with business, technology, and data leadership teams.

What You'll Do

- Design and implement enterprise-scale data platforms supporting Wealth Management initiatives.
- Build and optimize data ingestion, transformation, and analytics pipelines processing high-volume financial data.
- Develop AI/ML and GenAI solutions that improve client insights, operational efficiency, and decision support.
- Implement 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.

Nice to have

- Experience with Wealth Management platforms, investment products, portfolio analytics, and market data.
- Exposure to Elasticsearch, FAISS, Snowpark, Redshift, Aurora, and DB2.
- Experience converting legacy SAS/DataStage workloads into Spark or cloud-native 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 or cloud certifications.

📌 AI/ML Data Engineer - Wealth Management and Financial Services (Toronto)
🏢 Ju0026M Group
📍 Toronto