Our client is looking for a Senior Data Engineer to design, scale, and maintain high-performance ingestion, Change Data Capture (CDC), and delivery pipelines. In this role, you will architect enterprise-grade data platforms to process large-scale metadata, algorithmic feature extraction, and licensable asset datasets. This team sits at the foundation of the data processing and feature enrichment pipelines. Driving consistency and performance across an ever-growing data lake, we provide guardrails and sound system design patterns to inform the creation and fine-tuning of the industry's cutting-edge foundational large language models. You will leverage Google Cloud Platform (GCP) as the primary compute foundation of a multi-cloud data processing ecosystem, alongside hybrid data warehouses and query engines including Snowflake and ClickHouse to provide low-latency data exposure, incremental delta tracking, and seamless integration endpoints for downstream AI/ML consumption. Primary Tech Stack: GCP, ClickHouse, Snowflake, dbt Core, Apache Airflow, Python, SQL. Implement serverless and containerized data pipelines using GCP infrastructure (BigQuery, Dataflow, Pub/Sub, Cloud Storage, GKE). Enterprise ETL, CDC & Incremental Processing: Design robust Change Data Capture (CDC) and incremental update workflows to enable fast delta synchronization across platforms. Build dbt transformation models and Airflow orchestrations following Data Vault / dimensional modeling patterns. Maintain and optimize Snowflake integration layers, handling deduplication logic, canonical content filtering, and policy restrictions. Data Quality,



Governance & Scalability: Enforce metadata schema standardization, canonical asset mapping, and automated validation layers across diverse asset types (images, video, 3D models, audio). Google Cloud Platform (GCP): 4+ years of production experience with core GCP data technologies (BigQuery, Dataflow, Cloud Pub/Sub, GKE, Google Cloud Storage). Database & Query Engines: Deep technical proficiency with both Snowflake (warehousing, semi-structured queries, integration layers) and ClickHouse (real-time aggregation, low-latency columnar storage, indexing). Enterprise ETL / CDC: Proven experience architecting CDC pipelines and incremental delta loading for multi-terabyte dataset scale. Data Transformation & Orchestration: Hands-on mastery of dbt Core/Cloud and Apache Airflow in an enterprise CI/CD setting (e.g., GitHub Actions). Advanced skills in Python and SQL; familiarity with Go, Java, or Scala is a strong plus. Experience with Data Vault 2.0 architecture, hash-key generation, and raw/staging/integration layer design. Background handling AI/ML metadata, computer vision feature vectors, C2PA provenance headers, or semantic search configurations. Familiarity with media metadata schemas (images, 3D model stems, video derivatives). Experience with other major cloud providers such as AWS, Azure, or Oracle Cloud. ClickHouse & Snowflake Integration: Flexible working format
- remote, office-based or versátil Professional development tools (mentorship program, tech talks and trainings, centers of excellence, and more) not applicable for freelancers #

📌 Senior Engineer, Data Engineering (España)
🏢 NIX
📍 España