Senior Data Engineer, GCP, AI Platform

This is a fully remote position, open to applicants in United States.

📋 Description

• Develop the Analytics Platform (Greenfield): Architect and establish our inaugural analytical data platform on GCP (including warehouse, ingestion, transformation, and orchestration).

• Create Data Pipelines: Construct dependable ELT/CDC pipelines utilizing production Postgres and .NET/C# services with GCP-native tools (Datastream, Dataflow, Pub/Sub) and dbt for transformation.

• Set Up Orchestration & CI/CD: Implement workflows using Cloud Composer/Airflow or Dagster, along with data CI/CD environments and automated testing.

• Design Data for AI & Analytics: Develop dimensional models and a documented semantic/metrics layer to support dashboards, data analysts, and internal Claude agents with consistent definitions.

• Build the AI Data Layer: Establish and manage the retrieval substrate, embeddings pipelines, and vector storage (RAG data plumbing) to ensure internal and external agents access up-to-date data.

• Oversee Governance & Compliance: Enforce data validation, lineage, observability, and PII controls suitable for sensitive financial, donor, payment, and cross-border tax data.

• Collaborate Across Teams: Work alongside the AI Systems Engineer and the .NET backend team to instrument product events and deliver customer-facing insights.

⛳️ Requirements

• Over 6 years of Data Engineering experience, including at least one greenfield warehouse/platform development that you managed from start to finish.

• Proficient in SQL with extensive PostgreSQL experience, as well as strong familiarity with cloud data warehouses (BigQuery preferred).

• Solid ELT/ETL design capabilities using dbt and a contemporary orchestrator (Airflow/Cloud Composer or Dagster).

• Practical experience with the GCP data stack (BigQuery, Datastream, Dataflow, Pub/Sub, Cloud Storage).

• Skilled in Python for constructing data pipelines and developing custom tools.

• Proven experience with LLM/AI data: Embeddings pipelines, vector stores (e.g., pgvector, Vertex AI Vector Search, Pinecone), RAG plumbing, or feature stores supporting production ML/LLM systems.

• Strong understanding of data quality, lineage, observability, and PII data governance.

🏝️ Benefits

• Remote or Hybrid Work Options

• Private Health Insurance, including dental care

• Additional Holidays after your 1st and 5th year

• Sponsored Training & Certifications

• Employee Referral Bonuses

• Multisport Card – fully covered

• Fun Office Space with relaxation zones and free parking