Data Engineer - Cloud & SaaS Integrations(Remote Armenia)

Role overview

Join a remote R&D team as a Data Engineer focused on expanding the visibility of customer technology spend across cloud providers, SaaS tools, data clouds, and AI vendors. The core mission is to build integrations that translate a fragmented vendor landscape into a single, trustworthy view of cost that customers can act on financially. This role carries genuine, permanent ownership of the data side of an integrations framework, with a short path from shipped work to what end users see in production.

Responsibilities

- Design, build, and maintain new integrations against third-party billing and usage APIs, growing the share of customer spend that flows into the platform. - Operate in an AI-augmented style every day: use modern AI tooling to explore unfamiliar codebases and vendor APIs, prototype approaches, generate and review code, debug, write tests, and produce documentation, while exercising judgement about where automation earns its place. - Own the correctness and completeness of integration data, including deduplication, gap detection, race conditions in ingestion and reprocessing, marketplace overlap, and support for negotiated versus list pricing. - Build reconciliation checks and assertions that prove totals are right rather than relying on plausibility. - Design normalization models that make dozens of differently-shaped vendor bills comparable across units, currencies, time granularity, resource taxonomies, and cost categories. - Own pipeline orchestration, scheduling, and backfill mechanics end-to-end, including turning backfills into a routine and safe self-service operation. - Partner with product, support, and downstream engineers to surface gaps, propose work, and shape priorities rather than wait for a finished spec.

Requirements

- Three or more years of professional experience in data engineering or a data-heavy backend role, with production ownership of pipelines that other people depend on. - Strong SQL skills, including the ability to write, read, and reason about the performance of non-trivial analytical queries. - Hands-on experience building and operating pipelines with an orchestration framework such as Dagster or Airflow; equivalent depth in Prefect, dbt, or comparable tooling is acceptable with readiness to work in Dagster or Airflow. - Fluency in Python or another language commonly used for data work. - Experience with a cloud data warehouse or analytical store such as BigQuery, ClickHouse, Snowflake, or Redshift. - Track record integrating third-party REST APIs, including pagination, rate limits, partial failures, late-arriving and restated data, and vendors whose documentation is unreliable. - A real instinct for data correctness: reconcile totals, question plausible numbers, and build the check rather than assume the result. - An established AI-augmented working style, with concrete examples of how tooling has lifted engineering velocity. - Experience developing solutions in the cloud or using cloud services. - Clear written and verbal communication in English, and a self-organized, goal-oriented, and self-motivated approach.

Nice to have

- Experience with cloud or SaaS billing data, including AWS, GCP, or Azure cost and usage exports, marketplace billing, or the FOCUS specification. - Familiarity with Go for backend service development. - Background in systems with financial or audit-grade correctness requirements, such as invoicing, metering, revenue reconciliation, or billing engines. - Exposure to FinOps practices or cloud financial management products. - Bachelor's degree or equivalent practical experience.

Benefits and work setup

- Fully remote position with flexible working options. - Unlimited vacation policy. - Health insurance coverage, parental leave, and an inclusive, equitable workplace culture. - Employee stock option plan. - Home office allowance and a professional development stipend. - Peer recognition program.