A Data Architect develops computer databases for a company or organization. Designs, builds and implements databases and database systems that meet business requirements. Supports database administration, develops database security policies and works to prevent cyber attacks.
Hybrid Position Description Join a collaborative Data & Analytics team building a modern, cloud-native data platform on AWS. In this hands-on architecture role, you will shape the data foundations that power Wealth Management insights, working alongside engineers, analysts, and business stakeholders. You will have the autonomy to define standards and patterns while working with a modern lakehouse and streaming stack. This hybrid position offers a strong balance of technical depth, influence, and professional growth. Responsibilities Design and maintain the end-to-end data architecture for the Wealth Management domain, including data lakes/lakehouses, warehouses, and streaming pipelines on AWS. Define conceptual, logical, and physical data models for core wealth management entities such as clients, households, accounts, portfolios, holdings, transactions, and advisor relationships. Establish architecture standards, patterns, and best practices for data ingestion, storage, transformation, and consumption across the organization. Architect solutions for regulatory and compliance reporting (e.g., SEC, FINRA, Reg BI, SOX, and relevant privacy regimes), ensuring auditability and data lineage. Lead the design of data governance, quality, cataloging, and master data management (MDM) frameworks. Partner with security teams to enforce encryption, access controls, and PII/PCI handling for sensitive financial and client data. Guide data engineering teams on implementation, review designs, and ensure alignment with the target architecture. Evaluate and select tools and AWS services, balancing cost, performance, scalability, and maintainability. Support real-time and batch integration with source systems such as portfolio accounting, custody, CRM, market data feeds, and financial planning platforms. Collaborate with business and analytics stakeholders to enable BI, reporting, and advanced analytics/ML use cases. Required Skills 10-12 years of experience in Data Engineering/Data Architecture, with significant experience in Banking & Financial Services. Demonstrated experience in Wealth Management or closely related domains (Asset Management, Private Banking, or Brokerage), with working knowledge of financial instruments, portfolios, custody, advisory, and client/household data. Proven experience designing and implementing large-scale AWS-based data platforms. Strong expertise in data modeling, including Dimensional Modeling, Data Vault, and Normalized (3NF) approaches. Deep experience with Data Lake/Lakehouse and Data Warehouse architecture, including ETL/ELT design. Strong understanding of Data Governance, Data Quality, Metadata Management, and Data Lineage in regulated environments. Experience handling sensitive data with security, privacy, and compliance controls. Excellent stakeholder management and communication skills, with the ability to present architectural decisions to both technical and non-technical audiences.
Hands-on experience with AWS services:
S3 Redshift EMR Athena Glue Lake Formation Parquet Iceberg or Delta Lake Experience with Streaming and Serverless technologies: Kinesis MSK (Managed Kafka) Lambda Step Functions MWAA (Managed Airflow) Database experience:
Amazon RDS Aurora DynamoDB Security:
IAM KMS Encryption at Rest/In Transit Fine-Grained Access Control Infrastructure as
Code:
CloudFormation and/or Terraform Strong SQL and Python programming skills. Experience with BI tools such as QuickSight, Tableau, or Power BI. Nice-to-Have Skills AWS Certifications (AWS Certified Data Analytics - Specialty, AWS Certified Solutions Architect, etc.) TOGAF or other Enterprise Architecture framework experience. Experience with Data Catalog and Governance tools such as Collibra or Alation. Familiarity with market data providers such as Bloomberg or Refinitiv. Experience with Portfolio Accounting and Performance Management platforms. Exposure to Machine Learning and Advanced Analytics enablement. Experience implementing Data Mesh or Domain-Oriented Data Architecture. Knowledge of regulatory frameworks and reporting requirements within Wealth Management.
