Senior Data Engineer - fully remote!

Role overview A senior data engineering position on a foundational data platform team, reporting to the VP of Technology. The role owns the ingestion-to-catalog-to-derived pipeline and the core datasets powering a digital infrastructure marketplace, including a greenfield graph layer for routing. It is a fully remote, US-based opportunity suited to a hands-on architect who treats data quality, observability, and schema integrity as non-negotiable.

Responsibilities - Design, build, and maintain scalable ingestion, catalog, and derived pipelines with strict schema enforcement and data contracts. - Define and enforce data schemas and contracts across ingestion pipelines to ensure reliability for downstream confidence scoring and matching algorithms. - Engineer durable platform data systems that keep pipeline rework strictly under a 20% target threshold. - Migrate single-owner legacy systems onto scalable, multi-tenant platform architectures, including graph database layer design. - Partner daily with a distributed team across US, CET, and global time zones, and collaborate closely with data science/ML, intelligence engine, and trust/analytics partners. - Establish and uphold technical standards that safeguard the core data foundation across storage, orchestration, compute, and processing layers.

Requirements - 10+ years of dedicated data engineering experience as a senior individual contributor handling complex data platform architectures. - Advanced proficiency in SQL and Postgres, expert-level Python coding, and deep familiarity with modern data warehouse patterns (dbt or equivalent). - Extensive experience designing large-scale ELT/ETL pipelines, data contracts, schema governance, and robust data modeling paradigms. - Deep practical experience with AWS native services for storage, orchestration, compute, and data processing. - US-based, working US business hours, with fluent written and verbal English communication across a global team.

Nice to have - Hands-on experience with graph databases (Neo4j, AWS Neptune), ideally applied to network topology, geospatial routing, or graph-based search models. - Experience implementing real-time or event-driven ingestion architectures (Kafka, Kinesis, Flink). - Direct experience setting up enterprise data observability or data-quality frameworks (Great Expectations, Monte Carlo, Soda). - Experience building feature pipelines for ML matching models, alongside familiarity with telecommunications, datacenter, or digital infrastructure domain data.

Benefits and work setup - Fully remote work environment. - Health insurance fully covered for employees and their families, plus dental and vision options. - Unlimited paid time off. - Equity options that begin vesting after the first year.