FinOps Data Engineer, AI Cost & Usage Analytics

Job not on LinkedIn

🔥 0 minutes ago

🌐 Colombia, Costa Rica – Remote

🇨🇴 Colombia – Remote 🇨🇷 Costa Rica – Remote

⏰ Full Time

🟡 Mid-level

🟠 Senior

🚰 Data Engineer

👻 Ghost score 10%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Gorilla Logic

WebsiteLinkedInAll Job Openings

501 - 1000 employees

💼 Consulting

📣 Marketing

📦 Logistics

Consulting • Marketing • Logistics

Gorilla Logic is a company renowned for its expertise in modern software and data engineering. Serving as a strategic partner rather than just a vendor, Gorilla Logic specializes in digital product design, cloud engineering, data and AI delivery, DevOps, quality assurance, and legacy modernization. With a team of skilled digital product designers, solutions architects, and Agile nearshore teams, Gorilla Logic has been instrumental in developing business-critical software applications for Fortune 500 and SMB companies for over 20 years. Their services include creating SaaS platforms, enhancing digital experiences, and providing flexible, security-focused solutions. Gorilla Logic operates with teams located in Costa Rica, Colombia, Mexico, and the United States, emphasizing collaborative partnerships to deliver cutting-edge digital engineering solutions.

📋 Description

• Design, build, and maintain scalable data pipelines ingesting AI usage, billing, and consumption data from multiple providers and platforms • Develop API integrations and scheduled ingestion using Python, Cloud Functions, Cloud Composer/Airflow, or similar technologies • Implement error handling, retries, monitoring, and data-quality validation • Monitor vendor APIs and schemas and adapt integrations as providers evolve • Design and maintain a unified BigQuery model normalizing usage and billing data across AI providers and pricing models • Build dimensional and analytical models supporting cost allocation and reporting across teams, business units, projects, providers, models, and cost centers • Develop SQL/dbt/Dataform transformation workflows to cleanse, deduplicate, normalize, and enrich data • Integrate usage and cost data with organizational hierarchies and financial structures for chargeback/showback reporting • Optimize BigQuery through partitioning, clustering, incremental processing, and query optimization • Implement historical snapshots and slowly changing dimensions for trend and point-in-time analysis • Apply data governance, security, access control, auditability, and PII-handling practices • Build and maintain Power BI dashboards for AI spend, consumption trends, cost allocation, budgets, forecasts, and utilization • Optimize BigQuery-to-Power BI connectivity and data models • Develop executive-ready dashboards and detailed drill-down analysis • Implement row-level security and access controls in Power BI • Partner with FinOps and business stakeholders to define metrics, KPIs, and anomaly-detection logic • Support budgeting, forecasting, cost allocation, and AI spend optimization initiatives • Maintain documentation for data lineage, pipeline architecture, transformation logic, and reporting definitions • Automate manual reporting and improve platform reliability, scalability, and cost efficiency • Collaborate with cross-functional teams in an Agile environment on technical decisions, planning, and continuous improvement

🎯 Requirements

• This position is open to candidates located in Colombia or Costa Rica only • 3+ years of professional experience in Data Engineering, Analytics Engineering, Software Engineering, or a related role • Strong proficiency in SQL and experience designing and maintaining analytical data models • Hands-on experience with Google BigQuery or comparable cloud data warehouses such as Snowflake or Amazon Redshift • Strong experience building data pipelines using Python • Experience with workflow orchestration technologies such as Apache Airflow, Google Cloud Composer, Dagster, or similar tools • Hands-on experience integrating with REST APIs, including authentication, OAuth, pagination, rate limiting, and error handling • Experience designing reliable data ingestion, transformation, validation, and monitoring processes • Hands-on experience with Power BI, including semantic/data modeling, DAX, dashboard development, and report optimization • Understanding of cloud billing and cost data structures across platforms such as GCP, AWS, or Azure • Experience working with Git and version-controlled development workflows • Experience implementing CI/CD practices for data pipelines and transformation code • Understanding of dimensional modeling, incremental processing, historical data management, and data-quality practices • Strong problem-solving skills and the ability to work with complex or ambiguous data requirements • Strong communication and collaboration skills, with the ability to work effectively with both technical and business stakeholders • Nice-to-have qualifications include FinOps knowledge/certification, AI/LLM usage or billing API experience, dbt or Dataform, enterprise chargeback/showback, Terraform/IaC, governance/security/compliance, and cost analytics/anomaly detection/forecasting/cloud optimization