Senior Data Engineer – Glasgow (UK), Amsterdam (NL) or Prague (CZ)
What we’re looking for…
Senior Data Engineer
Our Global Data team headquartered in Glasgow, UK is currently looking to hire several Senior Data Engineers on a Permanent Full-time basis to work remotely from one of our current EU locations in either Glasgow (UK), Amsterdam (NL) or Prague (CZ).
In this exciting role, you will be working as part of our Data Engineering team to build infrastructure and solutions for the management and organisation of Monster’s data.
In order to succeed in this role, you will be required to gather requirements from stakeholders, design data structures and data models, design and build data pipelines and understand how to build secure, scalable, efficient and fault tolerant solutions within cloud environments.
Please note: this position is on a fully remote work basis and we will consider all applications from candidates based in one of our following EU locations:
- Glasgow, Scotland, United Kingdom
- Amsterdam, Netherlands
- Prague, Czech Republic
What you will be doing…
- Build and maintain robust, scalable, automated cloud-based data pipelines using industry best practices
- Ensure quality of technical solutions as data moves across environments
- Recommend ways to improve data reliability, efficiency and quality
- Partake in cross team code reviews to ensure all solutions developed meet required standards
- Contribute to the ongoing development of the Data Engineering team’s processes and skill sets by finding innovative ways to tell the story of Monster's data and ensure it is available to the right people at the right time
- Analyse source systems, define underlying data sources and transformation requirements, design suitable data models and document the design/specifications
- Provide insight into the changing data environment, data processing, data storage and utilisation requirements for Monster and offer suggestions for solutions
What’s essential for you to have…
- Diverse technical background with over 5 years of experience in the development of data platforms – preferably in an Agile environment
- Over 3 years of experience working in a Big Data ecosystem processing data – including file systems, data structures, automation, security, messaging, movement etc.
- Over 3 years of experience working within a production cloud data infrastructure – including design, implementation, and maintenance (preferable GCP)
- At least 3 years of experience with SQL development across multiple language variations – such as SQL Server, Oracle, MySQL and Big Query)
- At least 2 years of experience developing data pipelines with orchestration tools – such as Apache Airflow or GCP Composer
- Over 2 years of experience in Python development
- Hands-on experience implementing ETL (or ELT) best practices at scale
- Experience working with both structured and non-structured data in various formats – such as JSON, AVRO, CSV, TSV, PDF etc.
- Knowledge of CI\CD best practices.
- Relentless focus on continuous improvement of solutions and processes to improve data reliability, efficiency, quality, and the Data Engineering team at Monster
- Good communications skills across all levels of stakeholder (business & technical)
- Continually keep up with advancements in data engineering practices
- Create and maintain architecture and systems documentation
What will make you stand out…
- Experience of encrypting and obfuscating sensitive data
- Experience of deploying Infrastructure as Code preferably using Terraform
- Experience of developing ETL and ELT data pipelines using Apache Beam, GCP Dataflow, Apache Spark or GCP Dataproc
- Knowledge of Salesforce, Salesforce Marketing Cloud and Zuora
If you are interested in this fantastic opportunity and want to have Monster in your corner, please apply via our career site by clicking on the link below… We’d love to hear from you!
Additional job details:
- Location: Remote working (“work from home”) from either Glasgow (UK), Amsterdam (NL) or Prague (CZ)
- Job type: Permanent Full-time
- Salary: Competitive
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