Data Engineering and Platform Manager

World Business Lenders, LLC

. Report to the Chief Data and Analytics Officer within the IDEA department .

Posted 10/7/2026full-timeRemote • Costa Rica, El Salvador, Brazil, Argentina, Guatemala, NicaraguaSeniorLeadWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates extensive experience in data engineering and architecture, with a strong focus on team leadership, operational risk management, and the ability to design and optimize data platforms. Proficient in SQL, data governance, and cloud technologies, particularly in Azure and Databricks environments.

Highest-signal resume keywords

Data EngineeringTeam LeadershipData GovernanceSQLAzure and Databricks

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data ArchitectureETL/ELTData ModelingData IngestionPerformance EngineeringAutomated TestingCI/CDOrchestrationData Quality ControlsMetadata Management

Soft Skills

CoachingPerformance ManagementIncident ManagementCommunicationDecision-Making

Tools & Technologies

Cloud StorageData PlatformsAPIsMonitoring ToolsObservability Tools

Industry Keywords

Financial ServicesData GovernanceData QualityOperational RiskData Integration

Tech Stack

Tools & technologies

AzureCloudETLSQL

About the role

Key responsibilities & impact

Report to the Chief Data and Analytics Officer within the IDEA department
Lead two Team Leads and four Analysts across Data Platform Engineering and Data Integration & Governance
Manage, coach, and develop team members with clear ownership, technical standards, feedback, and accountability
Set priorities, allocate capacity, remove delivery blockers, and maintain operational coverage for critical data services
Own the platform roadmap and resource plan; hire, assess performance, develop Team Leads, and build succession coverage
Maintain hands-on involvement in priority delivery
Oversee data ingestion, transformation, orchestration, storage, and delivery from design through production support
Define business-ready data models, schemas, freshness, and performance requirements based on business endpoints and product requirements
Maintain platform availability, performance, monitoring, scalability, and cost discipline
Lead incident response and root-cause follow-up
Set target data architecture and modernization priorities
Balance capacity, performance, resilience, and platform cost
Set standards for data architecture, master/reference data, testing, deployment, documentation, lineage, access, retention, and change control
Partner with analytics, intelligence products, security, infrastructure, and business owners to provide dependable governed data
Own analytical-platform ingestion and data delivery, agree interface contracts, and coordinate incident routing at shared boundaries
Lead resolution of material data-service issues and recurring control weaknesses
Personally design or review important data models and architecture, troubleshoot complex pipeline and performance issues, and step into critical delivery when needed
Build a durable organization through hiring, coaching, delegation, standards, performance management, and succession development

Requirements

What you’ll need

Relevant education or professional training in computer science, engineering, information systems, data, or a related discipline is valued; a degree is not mandatory
Twelve or more years of progressive experience in data engineering, data platforms, or data architecture
At least five years of people leadership experience, including meaningful experience leading Team Leads, managers, or senior technical staff
Experience building, scaling, or materially modernizing a production data platform or data engineering function
Ability to coach Team Leads, develop senior technical talent, allocate capacity, establish engineering standards, manage incidents and operational risk, and make roadmap and prioritization decisions with senior business leaders
Recent hands-on technical delivery experience
Experience designing business-ready curated or gold-layer datasets from downstream products, calculators, APIs, reporting, or decision-support requirements
Experience operating data platforms with large datasets and demanding performance requirements, including query and data-model optimization, partitioning or clustering, caching, and low-latency analytical workloads
Experience integrating data from operational systems, third-party vendors, APIs, files, and batch feeds while managing data contracts, schema changes, reconciliation, lineage, and source-quality issues
Experience establishing data governance, including ownership, data-quality controls, metadata/documentation, lineage, access, retention, and production change controls
Deep practical experience with SQL, dimensional and analytical data modeling, ETL/ELT, orchestration, APIs, cloud storage and compute, automated testing, CI/CD, observability, monitoring, and incident management
Strong practical ability to design and lead delivery in an Azure and Databricks environment, including lakehouse patterns, workload performance, reliability, and cost optimization
Strong understanding of data quality, lineage, metadata, master/reference data, access control, security, retention, schema evolution, change management, performance engineering, and cloud cost management
Ability to translate business and product requirements into technical architecture and explain trade-offs to executives and engineers
Financial-services, lending, credit, portfolio, or other data-intensive regulated-industry experience is helpful but not required
Experience in lending or financial services, business-user support, and data reconciliation preferred
Submit CV in English

Benefits

Comp & perks

Compensation in USD
Paid time off (PTO)
Fully remote work environment