AI/ML Data Engineer - Wealth Management and Financial Services

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 modern 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.