Data Engineering and Platform Manager
New
W
WBLData engineering
Workable workplace: remote; Workable locations: San José, San José Province, Costa Rica. San Salvador, San Salvador Department, El Salvador. Brasília, Brasília, Brazil. Buenos Aires, Buenos Aires, Argentina. Guatemala City, Guatemala, Guatemala. Managua, Managua, NicaraguaFull-TimeManager
Salary not disclosed
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Job Details
- Experience
- Twelve or more years of progressive experience in data engineering, data platforms, or data architecture, including at least five years of people leadership.
- Required Skills
- SQLAzureCI/CDRESTful APIsData modelingDatabricks
Requirements
- Bring 12 or more years of progressive experience in data engineering, data platforms, or data architecture.
- Have at least five years of people leadership, including meaningful experience leading Team Leads, managers, or senior technical staff.
- Demonstrate success building, scaling, or materially modernizing a production data platform or data engineering function.
- Show recent hands-on technical delivery; this is not a management-only role.
- Have experience coaching Team Leads, developing senior technical talent, allocating capacity, establishing engineering standards, managing incidents and operational risk, and making roadmap and prioritization decisions with senior business leaders.
- Design business-ready curated or gold-layer datasets for downstream products, calculators, APIs, reporting, or decision support.
- Operate data platforms with large datasets and demanding performance requirements, using query and data-model optimization, partitioning or clustering, caching, or similar techniques.
- Integrate operational systems, third-party vendors, APIs, files, and batch feeds while managing data contracts, schema changes, reconciliation, lineage, and source-quality issues.
- Establish data governance practices covering ownership, data quality, metadata and documentation, lineage, access, retention, and production change controls.
- Bring 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.
- Have practical ability to design and lead delivery in Azure and Databricks, including lakehouse patterns, workload performance, reliability, and cost optimization.
- Translate business and product requirements into technical architecture and explain trade-offs to executives and engineers.
- Relevant education or professional training in computer science, engineering, information systems, data, or a related discipline is valued but not mandatory.
- Experience in lending, financial services, business-user support, data reconciliation, or another data-intensive regulated industry is helpful or preferred, not required.
Responsibilities
- Manage, coach, and develop two Team Leads and four Analysts.
- Set team priorities, allocate capacity, remove delivery blockers, and maintain operational coverage for critical data services.
- Own the platform roadmap and resource plan, including hiring, performance assessment, succession coverage, and regular 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 needs.
- Maintain platform availability, performance, monitoring, scalability, and cost discipline; lead incident response and root-cause follow-up.
- Set target data architecture and modernization priorities, balancing 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 deliver governed data and resolve material data-service issues.
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