Data Engineering and Platform Manager

This is a fully remote position, open to applicants in Costa Rica, +5 more countries.

📋 Description

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

• Supervise two Team Leads and four Analysts within Data Platform Engineering and Data Integration & Governance.

• Mentor, coach, and develop team members by establishing clear ownership, technical standards, feedback, and accountability.

• Prioritize tasks, allocate resources, eliminate delivery obstacles, and ensure operational coverage for essential data services.

• Take ownership of the platform roadmap and resource planning; recruit, evaluate performance, develop Team Leads, and establish succession coverage.

• Maintain active involvement in priority deliveries.

• Manage data ingestion, transformation, orchestration, storage, and delivery from the design phase through to production support.

• Define business-ready data models, schemas, freshness, and performance criteria based on business endpoints and product specifications.

• Ensure platform availability, performance, monitoring, scalability, and cost management.

• Lead incident responses and follow up on root-cause analyses.

• Establish target data architecture and modernization priorities.

• Balance capacity, performance, resilience, and platform expenses.

• Set standards for data architecture, master/reference data, testing, deployment, documentation, lineage, access, retention, and change management.

• Collaborate with analytics, intelligence products, security, infrastructure, and business stakeholders to provide reliable governed data.

• Oversee analytical-platform ingestion and data delivery, establish interface agreements, and manage incident routing at shared interfaces.

• Address significant data-service issues and recurring control weaknesses.

• Personally design or evaluate key data models and architecture, troubleshoot complex pipeline and performance challenges, and engage in critical delivery when necessary.

• Develop a sustainable organization through hiring, coaching, delegation, standards, performance management, and succession planning.

⛳️ Requirements

• Relevant education or professional training in computer science, engineering, information systems, data, or a related field is preferred; a degree is not essential.

• A minimum of twelve years of progressive experience in data engineering, data platforms, or data architecture.

• At least five years of experience in people leadership, including substantial experience leading Team Leads, managers, or senior technical personnel.

• Proven experience in building, scaling, or significantly modernizing a production data platform or data engineering function.

• Capable of coaching Team Leads, developing senior technical talent, allocating resources, setting engineering standards, managing incidents and operational risks, and making roadmap and prioritization choices with senior business leaders.

• Recent hands-on technical delivery experience.

• Experience in designing business-ready curated or gold-layer datasets from downstream products, calculators, APIs, reporting, or decision-support needs.

• Familiarity with operating data platforms that handle large datasets and demanding performance criteria, including query and data-model optimization, partitioning or clustering, caching, and low-latency analytical workloads.

• Experience in integrating data from operational systems, third-party vendors, APIs, files, and batch feeds while managing data contracts, schema modifications, reconciliation, lineage, and source-quality issues.

• Experience in establishing data governance, including ownership, data-quality controls, metadata/documentation, lineage, access, retention, and production change controls.

• Extensive 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 architectures, workload performance, reliability, and cost optimization.

• Comprehensive 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 communicate trade-offs to executives and engineers.

• Experience in financial services, lending, credit, portfolio management, or other data-intensive regulated industries is beneficial but not mandatory.

• Preferred experience in lending or financial services, business-user support, and data reconciliation.

• Submit your CV in English.

🏝️ Benefits

• Compensation offered in USD.

• Paid time off (PTO).

• Fully remote work environment.