Senior Data Engineer

1. Ingestion Architecture & GCP Foundation: * Architect, build, and optimize scalable job creation, batching, and high-throughput ingestion pipelines hosted on GCP. * Implement serverless and containerized data pipelines using GCP infrastructure (BigQuery, Dataflow, Pub/Sub, Cloud Storage, GKE).

2. 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. * Implement delta tracking methods (e.g., hash keys, hash diffs) to track row-level asset modifications and metadata events.

3. Multi-Engine Analytics & Query Optimization: * Maintain and optimize Snowflake integration layers, handling deduplication logic, canonical content filtering, and policy restrictions. * Deploy and manage ClickHouse as a high-concurrency analytical engine to deliver sub-second metadata retrieval and indexing. * Construct dedicated integration views and API query layers allowing internal and external clients to consume real-time delta updates.

4. Data Quality, Governance & Scalability: * Enforce metadata schema standardization, canonical asset mapping, and automated validation layers across diverse asset types (images, video, 3D models, audio). * Collaborate closely with cross-functional teams to integrate metadata pipelines with feature extraction tools, search indexes, and licensing platforms., Key Success Metrics (First 90 Days) * GCP Pipeline Optimization: Standardize ingestion batching and pipeline compute infrastructure on GCP. * ClickHouse & Snowflake Integration: Establish streamlined integration views exposing low-latency metadata delta changes. * Automated CDC Workflows: Finalize automated dbt delta transformations with hash tracking across primary warehouse layers.

Primary Tech Stack: GCP, ClickHouse, Snowflake, dbt Core, Apache Airflow, Python, SQL., * 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).
• Programming Skills: 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.

• Flexible working format - remote, office-based or flexible
• A competitive salary and good compensation package
• Personalized career growth
• Professional development tools (mentorship program, tech talks and trainings, centers of excellence, and more)
• Active tech communities with regular knowledge sharing
• Education reimbursement
• Memorable anniversary presents
• Corporate events and team buildings

• Other location-specific benefits

• not applicable for freelancers