Senior Data Platform Engineer

About the role

We are looking for an experienced Data Platform Engineer to design, build, and operate the infrastructure and pipelines that make data at Taxfix reliable, compliant, and ready for AI. You will own the systems that move data from operational databases, APIs, and SaaS tools into our analytical environment and make sure that data is correct, timely, and safe to use.

What you'll do

• Contribute to and operate cloud platform infrastructure - manage GCP resources (GCS, Dataflow, Dataproc, k8s, Pub/Sub…), provision and maintain environments with Terraform and help ensure the platform is reliable, predictable, cost-efficient and scalable
• Build and maintain ingestion pipelines that capture changes from application databases, APIs, SaaS and deliver clean, analytics-ready tables to our cloud data warehouse
• Operate and improve our orchestration layer - scheduling, retries, SLA tracking, and observability for data pipelines
• Design data models with proper layering that handle real-world data complexity: out-of-order events, schema evolution, late arrivals, and backfills
• Own data quality monitoring - build validation, monitoring, and alerting that catches problems before downstream consumers do
• Implement privacy and compliance controls - anonymization, pseudonymization, access policies, and deletion propagation (GDPR right-to-be-forgotten) across raw and derived layers
• Prepare data for ML and AI use cases - build governed, privacy-safe datasets and feature pipelines that ML engineers and data scientists can use for model training, evaluation, and production inference

What you'll need

• 4+ years of experience in Data Engineering or a similar role
• Strong Python skills for data pipeline development - you write production code, not just scripts
• Strong SQL skills - window functions, CTEs, query optimization are second nature
• Experience with event-driven data pipelines - CQRS, event ordering, idempotency, and the difference between initial load and incremental processing
• Expert with Airflow - you've built DAGs with proper task dependencies, retries, and monitoring
• Strong Snowflake or other modern data warehouse knowledge - resource management, security & governance, columnar storage & partitioning/clustering concepts, and query performance & cost optimization
• Cloud platform experience - you've worked with GCP (GCS, Dataflow, Dataproc etc) or equivalent AWS/Azure services
• Infrastructure-as-code experience with Terraform, Helm, or similar tools

Nice to have

• K8S and Docker containerization - you package and deploy your own work
• Data for AI readiness - you have experience preparing data for ML and AI use cases with appropriate governance, lineage, and privacy controls
• Awareness of data privacy requirements - you can identify PII, understand GDPR, and know how to implement anonymization and deletion across multiple data layers
• AI-enabled engineering practices - you actively use AI assistants and code generation tools to accelerate development

What they offer

• 30 annual vacation days and flexible working hours
• Free mental health coaching sessions and yoga
• Monthly allowance for services, flexible and roll-over
• Employee stock options for all employees
• Work from abroad for up to six weeks every year
• Free tax declaration filing through the Taxfix app