Data Platform Lead (Banking)
•Today
| Hours | Full-time |
|---|---|
| Location | Miami, Florida |
About this job
Job Description
Job Description
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.
Key Responsibilities:
Requirements
ITTConnect is seeking a Data 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.
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