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Senior Data Engineer

N-iXUA

EngineeringSenior4+ yrs
Source-verified: read directly from this employer's own greenhouse job board, not a repost.HybridPosted (9 days ago)Last verified (today)

At a glance

Location
UA
Workplace
Hybrid
Pay
Not published by the employer
Employment type
Not stated
Experience
4+ years
Education
No degree requirement stated
Job family
Engineering
Seniority
Senior
Posted by employer
14 October 2026
Last verified open
23 October 2026
Region and country
UA
Team
Shutterstock: Content Analytics Team
Listed via
Greenhouse

What the employer wrote

 

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.

Responsibilities 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.

Requirements - 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.

Nice-to-Have Qualifications: - 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.

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.

  We offer*:

• 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

Where this record came from

Read from N-iX's own Greenhouse job board on , and last confirmed still open on . The employer published it on 14 October 2026. Jobsearch.ing did not write, edit or rank this posting, and does not vet the employer. View the original posting.

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