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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Intelligence Platform Lead - **Company:** ITTCONNECT INC - **Location:** Miami, FL, United States - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Airflow, Amazon Web Services, Amazon S3, Data Analysis, Cloud Engineering, Cyber Security, Continuous Integration, Data Architecture, Information Engineering, Data Governance, Data Infrastructure, Data Security, Data Warehousing, Document-Oriented Databases, Identity and Access Management, Metadata, Microsoft SQL Server, Data Streaming, Cloud Platform System, Data Ingestion, Delivery Pipeline, Infrastructure Automation Frameworks, AWS Data Analytics, Data Management, Data Pipelines, Databricks - **Published:** August 30, 2026 - **Apply:** https://www.dice.com/job-detail/5229b625-7b58-4e33-83d3-211fffd2a4f9 ## About the Role * 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. ## Description 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., * 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. ## Related Videos - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [A Data Mesh needs Open Metadata](https://www.wearedevelopers.com/videos/505-a-data-mesh-needs-open-metadata) - [WeAreDevelopers LIVE - CSS is DOOMed](https://www.wearedevelopers.com/videos/1838-wearedevelopers-live-css-is-doomed) - [Enjoying SQL data pipelines with dbt](https://www.wearedevelopers.com/videos/823-enjoying-sql-data-pipelines-with-dbt) - [Hate organising your photos? 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