Data Engineer

Evolved Ideas

Data Engineer responsible for end-to-end customer identity data pipeline for a leading European platform. Collaborating with teams to ensure scalable and reliable data solutions.

Posted 7/27/2026full-timeRemote • 🇺🇦 UkraineMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in production data engineering with a focus on building scalable data pipelines, maintaining data quality, and implementing effective identity resolution models. Strong proficiency in BigQuery, SQL, and Python is essential for developing robust data solutions.

Highest-signal resume keywords

Production Data EngineeringBigQueryAdvanced SQLPythonAirflow

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data Pipeline DevelopmentProbabilistic Record LinkageEntity ResolutionData Quality ManagementIncremental PipelinesIdempotent Data ProcessingMatching LogicPrecision/Recall Trade-offs

Soft Skills

Strong CommunicationStructured Working ApproachOwnership-driven Mindset

Tools & Technologies

BigQueryGCSCloud RunAirflow

Industry Keywords

Customer Identity Master DataData EngineeringAnalytical EnvironmentsData Solutions

Tech Stack

Tools & technologies

AirflowBigQueryCloudPythonSQL

About the role

Key responsibilities & impact

Own the end-to-end pipeline that creates the unified customer_uuid across Books & Media and Fashion
Maintain and evolve our customer identity master data with a strong focus on accuracy, reliability, and production quality
Improve our probabilistic identity resolution model and make matching decisions measurable, transparent, and explainable
Build scalable and cost-efficient data pipelines across BigQuery, GCS, and Cloud Run Jobs
Introduce diagnostics, monitoring, and structured validation for every relevant model change
Identify and resolve edge cases in customer matching logic before they become production issues
Work closely with business and technical stakeholders to turn complex matching challenges into robust data solutions

Requirements

What you’ll need

5+ years of experience in production data engineering
Strong experience with BigQuery and advanced SQL in large-scale analytical environments
Strong Python skills for production-grade data engineering
Solid Airflow experience and a strong understanding of reliable orchestration patterns
Hands-on experience with incremental pipelines and idempotent data processing
Experience with probabilistic record linkage or entity resolution in production
Strong understanding of data quality, matching logic, and precision/recall trade-offs
A careful, structured, and ownership-driven way of working
Strong communication skills and the ability to explain technical decisions clearly

Benefits

Comp & perks

Healthcare insurance
Educational budget
Challenging tasks and professional development, knowledge & best practice sharing