Data Engineer (GCP, ML, Visualization)

Background

This role is part of the Instore Analytics capability area within the Co-Worker Operational Tools team, which focuses on developing data-driven in-house solutions built on Google Cloud Platform (GCP).

• Role: We are seeking a Data Analyst with a Data Engineering background to collaborate with in-house software engineers on data engineering and data analysis tasks.
• Reporting: Reports to the Engineering Manager responsible for this area.
• Timing: Work in CET time zone (8 AM – 5 PM CET) with occasional flexibility.
• Duration: Initial contract from 01 Feb to 31 Aug 2025, with potential for extension based on performance and business needs.
• Location: Open to Malmö, Madrid, or offshore. No travel or international mobility required.

Scope of Work

The consultant will:

• Collaborate with engineers on data-related topics, including developing, maintaining, and improving products to ensure efficient data flow, process automation, and visualization.
• Own all data-related activities, including deployment, release management, security, and privacy.
• Drive innovation and automation to enhance data workflows.
• Utilize Jira, GitHub, and Confluence for work tracking and documentation.
• Adhere to best practices and architectural guidelines for data and technology.
• Create and maintain KPIs in Looker Studio or Power BI.
• Work on Machine Learning (ML) and Large Language Models (LLMs), including ML model creation and optimization, such as waiting time estimation models.

Requirements:

Desired Skills & Competencies

• Google Cloud Platform (GCP) expertise: BigQuery, Cloud Storage, Cloud Functions, Cloud Scheduler, Dataflow, and Dataform.
• Data visualization tools: Power BI & Looker Studio.
• Programming languages: Python (Pandas, Jupyter Notebooks, Matplotlib, Scikit-learn, Numpy, TensorFlow).
• Database systems: Relational databases (MySQL, PostgreSQL) & NoSQL (Firestore).
• Machine Learning: Experience in creating and maintaining ML models & LLMs.
• Data analysis & critical thinking: Ability to extract, analyze, and use data to support business decisions.
• Data quality: Strong understanding of data quality analysis and best practices.

Top 3 Key Requirements

1. End-to-end data processing: Ability to extract, transform, load (ETL) and visualize data.
2. Working with diverse data sets: Handling various data sources and owning data-related tasks within a product.
3. GCP expertise & visualization: Proficiency in Google Cloud components and data visualization tools.