Senior Data Engineer

Accesa is a leading technology company headquartered in Cluj-Napoca, with offices in Oradea and 20 years of experience in turning business challenges into opportunities and growth.

A value-driven organisation, it has established itself as a partner of choice for major brands in Retail, Manufacturing, Finance, and Banking. It covers the complete digital evolution journey of its customers, from ideation and requirements setup to software development and managed services solutions.

With more than 1,200 IT professionals, Accesa also has a fast-growing footprint, establishing itself as an employer of choice for IT professionals who are passionate about problem-solving through technology. Coming together in strong tech teams with a customer-centric approach, they enable businesses to grow, delivering value for our clients, partners, industry, and community.

The client is developing its own Marketing AI product to deliver personalized product, bundle, and promotion recommendations based on customer profiles, purchase history, and behavioral data. The goal is to make recommendations more relevant, increase conversion, and improve profit margins.

Within this initiative, we are looking for Data Engineering profiles, one focused on building the customer data foundation and another on integrating customer platforms and communication channels.

As a people-first organisation, we believe diversity strengthens our teams and drives innovation. All employment decisions are based on merit, skills, and performance, without discriminating based on any personal characteristic. This reinforces our commitment to providing an inclusive and respectful workplace.

Responsibilities

Design and build a scalable customer data mart that consolidates loyalty attributes, wishlist and affinity data, and explicit preferences captured in the app.; Set up real-time data streaming between backend systems, the CDP (Zeotap) and the CEP (Responsys).; Build and maintain robust backend APIs that give product teams access to customer data for personalization.; Model and transform data in BigQuery and Dataform, and orchestrate pipelines with Cloud Workflows, Cloud Scheduler and Eventarc.; Manage infrastructure as code with Terraform and ship through CI/CD pipelines in GitHub Actions.

Requirements

Expert Python and SQL skills in production data engineering.; Hands-on experience with GCP data services, in particular BigQuery, Pub/Sub, Cloud Run and Cloud Storage.; Experience with Dataform, Datastore, Cloud Workflows, Eventarc and Cloud Scheduler.; Experience building real-time or event-driven data pipelines.; Experience designing data models and data marts for analytical and operational use.; Experience building REST APIs in Python, ideally with Flask.; Infrastructure as code with Terraform (HCL) and CI/CD with GitHub Actions.; Fluent English for working in an international team.

Nice to have

Experience integrating a Customer Data Platform (Zeotap).; Experience with Oracle Responsys or another CEP (Salesforce Marketing Cloud, Braze).; Background with customer, loyalty or e-commerce data, including identity resolution.; GCP Professional Data Engineer certification.