Data & FinOps Engineer

At Lumenalta, we partner with forward-thinking organizations to build technology solutions that scale, delight users, and accelerate business growth. Our global teams bring curiosity, commitment, and technical excellence to every project. We value transparency, autonomy, and impact—empowering every team member to do their best work.

We’re seeking an experienced Data & Fin Ops Engineer to join a high-impact GCP platform engagement. This role sits at the intersection of data engineering and cloud financial operations—owning audit log pipelines, legally defensible immutable storage, cost attribution infrastructure, and real-time cloud spend visibility. You’ll build the observability and governance backbone that keeps a complex, multi-tenant platform compliant, traceable, and cost-efficient.

We are hiring for a current opening on an active client project. This is a specific, presently open role. We review applications on a rolling basis and aim to move qualified candidates through our process promptly.

• Design and maintain Big Query audit datasets
  —including schema design for legally defensible logging, Object Lock/immutability configuration for tamper-proof retention, and access controls aligned with compliance requirements.
• Build and operate Cloud Audit Log pipelines
  , routing MCP inputs and outputs continuously into structured, queryable audit stores for security, compliance, and operational review.
• Engineer Cloud Billing export pipelines and construct Looker Studio dashboards that surface real-time cost visibility, spend trends, and budget forecasting for engineering and stakeholder audiences.
• Implement Fin Ops tagging and labeling strategies across GCP resources—enabling granular cost attribution by tenant, project, and user to support chargeback, showback, and optimization workflows.
• Configure Cloud Monitoring alerting for quota exhaustion and cost anomalies, ensuring engineering teams are notified proactively before limits or budget thresholds are breached.
• Build metadata pipeline engineering workflows that feed structured metadata into archive management systems, maintaining data lineage, retention schedules, and lifecycle policy enforcement.
• Design, build, and maintain reliable ETL pipelines from the ground up—ensuring data quality, consistency, performance, and reliability across the platform.
• Partner with data, product, and engineering stakeholders to deliver high-quality, actionable data infrastructure that serves both operational and compliance needs.

• 7+ years as a Data Engineer, with demonstrated experience building production data pipelines and a growing specialization in cloud cost management and audit/compliance infrastructure.
• Strong hands-on experience with Big Query—including audit dataset design, schema modeling for compliance use cases, and Object Lock/immutability configuration for legally defensible log retention.
• Experience routing and processing GCP Cloud Audit Logs into structured pipelines, with an understanding of log sink design, filtering, and continuous delivery patterns for MCP or equivalent workloads.
• Proven ability to implement Cloud Billing exports, design Fin Ops tagging/labeling taxonomies, and build Looker Studio dashboards that provide tenant-, project-, and user-level cost attribution.
• Experience configuring quota-exhaustion and cost-anomaly alerting in Cloud Monitoring—designing alert policies, notification channels, and escalation thresholds for multi-tenant environments.
• Familiarity with metadata pipeline engineering feeding into archive management systems, including lifecycle policy enforcement and retention schedule automation.
• Strong proficiency in Python for pipeline development and advanced SQL for querying large datasets in Big Query and related GCP data services.
• Experience implementing data quality checks, monitoring, and CI/CD pipelines for data workflows to ensure platform reliability.
• Strong written and verbal communication skills in English.

• Experience with Airflow, Kafka, or similar orchestration and messaging tools.
• Familiarity with data governance, DLP policies, or privacy…