Remote AI-Driven Data Engineer for Cloud Spend & Integrations

Remote Genie; Dublin; Hybrid; EUR 70,000 - 110,000; Full time

Benefits offered by this job

Unlimited Vacation

Flexible Working Options

Health Insurance

Employee Stock Option Plan

Professional Development Stipend

Job summary

DoiT is hiring a Data Engineer to own the data side of integrations, expanding visibility of customer spend across more vendors. You will work remotely as a full-time employee in supported regions, applying AI across workflows and maintaining data correctness from ingestion to reconciliation.

You will collaborate with product, support, and engineering teams to build scalable, well-documented pipelines and normalization models, while driving velocity and quality in a distributed environment.

Qualifications

• 3+ years of professional experience in data engineering or a data-heavy backend role with production ownership of pipelines.
• Strong SQL: write, read, and optimize non-trivial analytical queries.
• Hands-on experience building and operating data pipelines with Dagster or Airflow.
• Strong Python or another language used for data work.
• Experience with a cloud data warehouse or analytical store (BigQuery, ClickHouse, Snowflake, Redshift or similar).
• Experience integrating third-party REST APIs with pagination, rate limits, and variability.
• AI-augmented working style and ability to apply AI across engineering workflow.
• Experience developing solutions in the cloud and using cloud services.
• Excellent English communication, written and verbal.
• Self-organized, goal-oriented and self-motivated.

Responsibilities

• Expanding vendor coverage by building integrations against third-party billing and usage APIs.
• Using AI daily across the full span of work: prototyping, generating code, debugging, tests, and documentation.
• Ensure data correctness and completeness: deduplication, gaps, race conditions, and negotiated rates.
• Design and build normalization models for dozens of vendor bills: units, currencies, time granularity, taxonomies, cost categories.
• Own ingestion pipelines orchestration, scheduling, and backfills end-to-end.
• Collaborate with product, support, and engineers to identify gaps and propose work.

Skills

SQL

Python

Dagster/Airflow

Data pipelines

Cloud data warehouse

REST APIs

AI-augmented workflow

English communication

Data quality

Tools

Dagster

Airflow

Job description

DoiT is hiring a Data Engineer to own the data side of integrations, expanding visibility of customer spend across more vendors. You will work remotely as a full-time employee in supported regions, applying AI across workflows and maintaining data correctness from ingestion to reconciliation.

You will collaborate with product, support, and engineering teams to build scalable, well-documented pipelines and normalization models, while driving velocity and quality in a distributed environment.