Description

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 requirement
• 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

Key Skills

Education

Not specified