Data Engineer

Position: Data Engineer (f/m/d)
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Data sits at the heart of the company. This role is to ensure that Awin is able to leverage the data it has access to across the group and build out reporting to ensure we are able to make better commercial decisions and provide best‑in‑class campaign management to support client facing departments.
As a Data Engineer, you are responsible for collecting data from multiple sources, sanitizing, cleansing, transforming, and consolidating it to make it available for further analysis or publication in reports.
You understand data, business and technical requirement. You write clean and high‑quality code that is easy to understand and maintain. You clearly understand the various methodology of data extraction, transformation and storage and successfully applying your experience and knowledge of scripting, SQL, and conceptual OLTP and/or OLAP database.
In this role, you will help ensure the smooth day‑to‑day operation of the data warehouse while working closely with a global team of data engineers, analysts, and reporting specialists — as well as other big data engineers within the organization.
Key Tasks & Accountabilities

Write clean, elegant, and maintainable code following data warehousing best practices and modeling techniques (Kimball, Star Schema, etc.).
Troubleshoot data transformation errors by debugging and developing effective solutions.
Clearly and confidently present findings, bugs, and proposed system improvements to stakeholders.
Design and implement new Azure and AWS data pipelines and Databricks notebooks to integrate additional data sources.
Add new data points to existing Azure Analysis Services (AAS) cubes or equivalent data models.
Continuously identify and implement performance improvements.
Ensure the quality, accuracy, and reliability of all data and reports.

Education & Experience

Bachelor’s degree or higher in Data Science, Data Engineering, Business Intelligence, Business Administration, or a related field with a focus on data engineering, analytics, or business intelligence.
2+ years of working experience as a Data Engineer or Data Warehouse Developer using Python or similar technologies.
Hands‑on experience with Microsoft Azure and AWS data engineering pipelines.
Excellent knowledge of database and dimensional modeling techniques.
Strong experience with Azure Data Factory, Azure Databricks, Python (Num Py, Pandas), ADLS, Azure Event Hub, and Azure SQL DB.
Familiarity with AWS Glue, S3, Athena, Redshift, and Lambda is highly desirable.
Excellent command of SQL, T‑SQL, Python, and PySpark.
Practical experience with Agile and Scrum methodologies.
Strong communication and analytical skills.
Ideally, experience working in a big data environment and exposure to AI/ML frameworks/libraries (MLlib, MLOps, Scikit‑learn, Tensor Flow, Matplotlib), Spark, and JSON.

Skills & Core Competences

Ability to design, build, and optimize complex data pipelines in Python and PySpark using Azure and AWS services (e.g., Data Factory, Databricks, S3, and ADLS).
Strong analytical mindset with the ability to translate business needs into actionable data solutions.
Solid mathematical and problem‑solving skills, with a curiosity to learn and apply new concepts.
Innovative mindset — proactively bringing new ideas and improvements to data warehouse development.
Open to change, eager to learn, and willing to take initiative.
Self‑reliant and confident in making autonomous decisions when needed.
Excellent communication and interpersonal skills.
Strong project and process management skills — consistently delivering work on time and within budget without compromising quality.
Collaborative team player committed to continuous improvement.

Our Offer

Flexi‑Week and Work‑Life Balance:
We prioritise your mental health and wellbeing, offering you a flexible four‑day Flexi‑Week at full pay and with no reduction to your annual holiday allowance. We also offer a variety of different paid special leaves.
Flexi‑Office:
We offer an international culture and flexibility through our Flexi‑Office and hybrid/remote work…