Job Description

Data Engineer - ETL
Location: Guildford
Employment Type: Full-time
PCD280124

Role Overview
An opportunity is available for an experienced data engineer - etl to support a busy and professional team.

Key Responsibilities
• As a Data Engineer you will be involved in the entire development life cycle, from brainstorming ideas to implementing elegant solutions to obtain data insights.
• You will gather requirements, model and design solutions to support product analytics, business analytics and advance data science.
• Design efficient and scalable data pipelines using cloud-native and open source technologies.
• Develop and improve ETL/ELT processes to ingest data from diverse sources.
• You will work with analysts, understand requirements, develop technical specifications for ETLs, including documentation.
• You will support production code to produce comprehensive and accurate datasets.
• Automate deployment and monitoring of data workflows using CI/CD best practices.
• You will promote strategies to improve our data modelling, quality and architecture.
• Participate in code reviews, mentor junior engineers, and contribute to team knowledge sharing.
• Document data processes, architecture, and workflows for transparency and maintainability.
• You will work with big data solutions, data modelling, understand the ETL pipelines and dashboard tools.

Skills and Experience
• We are looking for an experienced Data Engineer with broad technical skills and ability to work with large amounts of data. You will collaborate with the Game and Product[1] teams to implement data strategies and develop complex ETL pipelines that support dashboards for promoting deeper understanding of our games.
• You will have experience developing and establishing scalable, efficient, automated processes for large-scale data analyses. You will also stay informed of the latest trends and research on all aspects of data engineering and analytics. You will work with leaders from an internal Game Studio, providing them with data for understanding game and player insights and report to the Technical Lead for this group. This is a hybrid role based in our Southam office.
• 4+ years relevant industry experience in a data engineering role and graduate degree in Computer Science, Statistics, Informatics, Information Systems or another quantitative field.
• Proficiency in writing SQL queries and knowledge of cloud-based databases like cloud data platform, Redshift, cloud data warehouse or other big data solutions.
• Experience in data modelling and tools such as dbt, ETL processes, and data warehousing.
• Experience with at least one of the programming languages like programming language, C++[2], programming language.
• Experience with version control and code review tools such as version-control system.
• Knowledge of latest data pipeline orchestration tools such as workflow orchestration platform.
• Experience with cloud platforms (cloud platform, cloud platform, or cloud platform) and infrastructure-as-code tools (e.g., containerisation technology, infrastructure automation tool, CloudFormation).
• Familiarity with data quality, data governance, and observability tools (e.g., Great Expectations, Monte Carlo).[3].
• Experience with BI and data visualization tools (e.g., analytics platform, data visualisation platform, business intelligence platform).
• Experience working with product analytics solution (Amplitude, Mixpanel).
• Experience working on mobile attribution solutions (Appsflyer, Singular)[4].
• Experience working on a mobile game or a mobile app, ideally from early stages of the product life cycle.
• Experience working in an Agile development environment and familiar with process management tools such as work-management software, Target process, work-management platform or similar.
• Nice to Have.
• Familiarity with data security, privacy, and compliance frameworks.
• Exposure to machine learning pipelines, MLOps, or AI-driven data products.
• Experience with big data platforms and technologies such as EMR, data analytics platform, event-streaming platform, Spark.
• Exposure to AI/ML concepts and collaboration with data science or AI teams.
• Experience integrating data solutions with AI/ML platforms or supporting AI-driven analytics.