Data Lake on AWS with Databricks - Financial Services

The Version 1 Financial Services AWS Data Lake Implementation is a production‑ready, governed data platform that consolidates fragmented financial services data into a single, AWS‑native lakehouse built on Amazon S3 and Databricks. It is designed for regulated financial institutions that need consistent, trusted data to power reporting, MI, workflow analytics and advanced data science, without sacrificing security or operational control.

The solution unifies data from SaaS applications such as ServiceNow, core banking and line‑of‑business systems, databases, file shares and API‑based sources into a structured set of S3 zones (Raw, Standardised, Curated), creating a clear lineage from original records through to analytics‑ready datasets. Multi‑source ingestion patterns span batch loads, event‑driven feeds and API integrations, giving teams a single platform to onboard data from legacy and modern systems at scale. Automated pipelines orchestrated with Databricks Spark, AWS Glue, AWS Lambda, AWS Step Functions and Amazon EventBridge handle ingestion, transformation, quality checks and publishing, minimising manual effort while improving reliability and time to value.

Metadata and governance are central to the design, with Databricks Unity Catalog and AWS Glue Data Catalog providing unified discovery, lineage and policy enforcement across all datasets and workspaces. This enables consistent data definitions, simplifies impact analysis and supports data stewardship and regulatory reporting obligations common in financial services. Curated data is exposed through Databricks, Amazon Athena, Amazon QuickSight, BI tools and APIs, enabling self‑service analytics for operations, risk, finance and product teams while preserving robust access controls.

Security and compliance are built in using AWS‑native controls aligned to AWS Well‑Architected best practices, including integration with customer AWS Organizations guardrails, AWS CloudTrail, AWS GuardDuty, AWS Security Hub, AWS KMS, IAM standards and S3 access logging. A “break glass” model for privileged access, combined with clear separation of duties and audited administration paths, helps institutions meet internal risk, audit and regulatory requirements. The platform is deployed into a customer‑provided landing zone, with readiness validation performed before implementation to ensure it integrates cleanly into existing governance frameworks.

Version 1 provides experienced consultants with expertise in AWS, Databricks and regulated financial‑services workloads, ensuring the platform is robust, performant and production‑ready from day one. Engagements include a formal AWS Well‑Architected Review during both design and pre‑handover stages, comprehensive documentation, runbooks, architecture diagrams and dataflow definitions, plus targeted enablement for engineering, analytics and operations teams. This equips customers to operate and evolve the data lake independently, accelerating the delivery of trusted insights, modern MI and innovative data products across their financial services organisation.