Databricks Solution Architect – Financial Crime & Banking

EXL (NASDAQ: EXLS) is a global data and artificial intelligence ("AI") company that offers services and solutions to reinvent client business models, drive better outcomes and unlock growth with speed. EXL harnesses the power of data, AI, and deep industry knowledge to transform businesses, including the world’s leading corporations in industries including insurance, healthcare, banking and financial services, media and retail, among others. EXL was founded in 1999 with the core values of innovation, collaboration, excellence, integrity and respect.

We are headquartered in New York and have more than 60,000 employees spanning six continents. For more information, visit www.exlservice.com.

Role Title: Databricks Solution Architect - Financial Crime & Banking

BU/Segment: Data Management / Banking & Financial Services

Location: Dublin, Republic of Ireland (Flexible hybrid working)

Employment Type: Contract

Summary of the role:

We are seeking a highly experienced Databricks Solution Architect to lead the design and delivery of large-scale Data, Analytics and Financial Crime solutions for Banking and Financial Services clients.

The successful candidate will be responsible for defining end-to-end Databricks Lakehouse architectures, and delivering Financial Crime platforms covering Anti-Money Laundering (AML), Know Your Customer (KYC), Customer Risk Assessment (CRA), Sanctions Screening, Transaction Monitoring, Fraud Detection, and Regulatory Reporting.

This is a client-facing consulting role requiring strong architecture leadership, domain expertise, solutioning capabilities, and the ability to translate business requirements into scalable cloud-native solutions.

As part of your duties, you will be responsible for:

Solution Architecture & Consulting

• Lead end-to-end architecture design for Databricks-based Financial Crime and Banking platforms.

• Define enterprise data architectures leveraging Lakehouse, Delta Lake and Unity Catalog.

• Conduct discovery workshops with business, compliance, and technology stakeholders.

• Translate regulatory and operational requirements into scalable technical solutions.

• Develop target-state architectures, migration roadmaps, and implementation strategies.

Financial Crime & Risk Management

• Architect solutions supporting:

  • AML Transaction Monitoring

  • Customer Risk Assessment (CRA)

  • KYC and Customer Due Diligence

  • Ongoing Due Diligence (ODD)

  • Sanctions and PEP Screening

  • Fraud Detection

  • Financial Crime Investigations

  • Regulatory Reporting

• Design Customer 360 and Financial Crime Lakehouse solutions.

• Enable real-time monitoring and risk analytics using streaming architectures.

Databricks Platform Architecture

• Design enterprise Databricks environments across Azure, AWS, or GCP.

• Architect:

  • Delta Lake

  • Unity Catalog

  • Lakehouse Architecture

  • Lakeflow / DLT

  • MLflow

  • Databricks SQL

  • Auto Loader

  • Vector Search and AI capabilities

• Define security, governance, lineage, and access-control frameworks.

• Ensure scalability, platform resilience, and cost optimization.

Data Engineering Leadership

• Define ingestion frameworks using:

• CDC

• Event Streaming

• Kafka

• Azure Event Hub

• Batch Processing

• Design Bronze/Silver/Gold data models.

• Oversee development teams implementing Spark and PySpark pipelines.

• Establish reusable accelerators and architectural standards.

Qualifications and experience we consider to be essential for the role:

• Bachelor's or Master's degree in Computer Science, Engineering, Analytics, Mathematics, or related discipline.

• 12+ years of Data and Analytics experience.

• 5+ years of hands-on Databricks architecture experience.

• 5+ years within Banking, Financial Services, AML, Fraud, or Financial Crime programs.

• Proven experience designing enterprise-scale cloud data platforms.

Skills we would like to have:

Databricks

Delta Lake, Databricks SQL, Unity Catalog, Lakeflow / DLT, MLflow, Auto Loader, Photon Engine, Vector Search

Data Engineering

PySpark, Python, Scala, Data Modeling, CDC Architecture, Batch and Streaming Pipelines

Cloud Platforms

Azure (preferred)

DevOps & Automation

Azure DevOps, GitHub, CI/CD, Terraform, Infrastructure as Code

Preferred Certifications

• Databricks Certified Data Engineer Professional

• Databricks Certified Solution Architect

• Databricks Certified Machine Learning Professional

Bachelor's or Master's degree in Computer Science, Data Science, Information Technology, or a related field. 12-14 years of experience in data warehousing or data management.