Data / Business Intelligence Lead (Banking)

Job Description

Job Description

ITTConnect is seeking a Data / Business Intelligence Platform Lead for a direct-hire full time position with a client that is a large financial institution.

Position is hybrid in Miami.

Our client is at a strategic moment in our data platform transformation, migrating from an on premise environment to a modern cloud native stack based on AWS, Databricks, and PySpark. They are seeking a hands-on, business-oriented data platform leader to lead a 10 people team in order to manage the bank's end-to-end data intelligence platform.

The successful candidate will coordinate the modernization of the current on-premises data environment while leading the design and implementation of a governed cloud data platform on Databricks and AWS. This is a strategic role for a professional who can connect architecture, governance, delivery execution, data quality, security, and AI adoption into a coherent enterprise data capability.

Key Responsibilities:

Cloud Data Platform and Migration

• Coordinate the structuring of the Databricks environment on AWS, including development pipelines, operational controls, governance parameters, data quality monitoring, alerting, and platform observability.
  
• Define and align target-state solutions for ingestion, orchestration, processing, monitoring, security, and lifecycle management in the Databricks ecosystem.
  
• Lead the migration of on-premises data pipelines to Databricks, ensuring they are rebuilt as reusable, scalable, governed, and well-documented data products.
  
• Partner with technology, security, infrastructure, compliance, and business stakeholders to ensure the cloud platform meets banking-grade operational, regulatory, and information security expectations.

Data Products, Governance, and Quality

• Coordinate the definition, documentation, and dissemination of the data product concept across the Data team and the broader bank.
  
• Establish the required governance, ownership, metadata, lineage, access, quality, monitoring, and lifecycle dimensions for data products.
  
• Review and strengthen governance practices in the current data warehouse environment, including data access workflows, pipeline development standards, orchestration processes, and data domain definitions.
  
• Define and document data quality dimensions, implement automated quality tests, and build end-to-end monitoring and alerting for critical data flows.
  

On-Premises Platform Modernization

• Coordinate DataSecOps practices to establish end-to-end monitoring and alerting across infrastructure, development environments, orchestration layers, and data pipelines.
  
• Lead the inventory, technical assessment, rationalization, and recommendation process for SQL Server environments, including whether to migrate, retain, consolidate, modernize, or decommission each server.
  
• Drive improvements in operational reliability, documentation, development standards, and production support for the current SQL Server, Airflow, and dbt environment.
  

AI Enablement and Governance

• Coordinate the establishment of AI governance practices, including principles, controls, accountability, observability, and risk management considerations.
  
• Identify, prioritize, and coordinate AI initiatives that generate measurable business value on top of both the current on-premises environment and the future cloud data platform.
  
• Support experimentation and delivery of AI-based use cases in collaboration with business, data, technology, compliance, and risk stakeholders.
  

Requirements

• 15+ years of experience in IT.
  
• Strong experience leading data platform, data engineering, analytics engineering, or data architecture initiatives in complex enterprise environments.
  
• Practical understanding of Databricks, AWS data services, SQL Server, Airflow, dbt, data ingestion patterns, orchestration, monitoring, and platform operations.
  
• Demonstrated ability to translate data governance, data quality, metadata, lineage, access control, and observability requirements into practical engineering standards.
  
• Experience coordinating platform migrations or modernization initiatives from legacy or on-premises environments to cloud-based architectures.
  
• Experience with Databricks Lakehouse architecture, Unity Catalog, data quality frameworks, CI/CD pipelines, and cloud-native monitoring practices.
  
• Experience with AWS services commonly used in data platforms, such as S3, IAM, networking, security controls, monitoring, and infrastructure automation.
  
• Familiarity with regulatory, security, and audit expectations in banking or financial services.
  
• Highly desirable fluency in Portuguese and/or Spanish.