Senior Data Engineer
Senior Data Engineer
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Job Description
Senior Data Engineer
London
(Hybrid)
We are Manufacturing the Future!
Geomiq is revolutionizing traditional manufacturing by providing engineers worldwide with instant access to reliable production methods through our digital platform. As the UKs leading Digital Manufacturing Marketplace we offer an AI-powered B2B MaaS (Manufacturing as a Service) solution seamlessly connecting buyers and suppliers to drive efficiency and innovation.
With our headquarters in London and quality branches in India China and Portugal we collaborate with leading brands like BMW Rolls-Royce Brompton Bikes and Googleeven contributing to space exploration.
Check out our website!
Our platform:
Geomiq offers a revolutionary platform that completely digitizes the quoting and ordering process for custom manufactured parts ensuring the highest operational and quality outcomes. Our primary customers include Design Engineers Mechanical Engineers and Procurement teams all of whom are involved in creating the worlds most innovative products.
See our platform in action!
About the role:
As a Senior Data Engineer at Geomiq you will play a central role in shaping our data infrastructure and operations. Your primary focus will be on establishing a robust foundation that is not only fit for the current needs but also sustainable for future growth. Youll be responsible for collecting data from various sources ensuring its structure and making it easily accessible for Business Intelligence and Data Science purposes.
Main responsibilities:
- Data Infrastructure Ownership: Take ownership of the end-to-end data infrastructure from aggregating data to designing building and maintaining scalable and efficient pipelines.
- Cross-functional data collaboration: Collaborate with data scientists analysts and product teams to understand their data requirements and deliver solutions that meet their needs.
- Data Warehousing: Design implement and optimise data warehousing solutions to support efficient data storage retrieval and analysis as well as working with 3rd party tools such as Hubspot and Mixpanel.
- Continuous Improvement: Stay abreast of industry best practices proactively identifying opportunities for improvement in data processes.
Experience Required:
- Bachelors degree in Computer Science Engineering or a related field (or equivalent experience)
- 5 years of experience in a data engineering role
- Experience in designing and implementing data models for relational and non-relational databases
- Proficiency in languages commonly used in data engineering specifically SQL and Python
- Familiarity with data warehouse concepts and technologies particularly Google BigQuery. ( Experience with Amazon Redshift can also be considered)
- Understanding of a variety of databases including both SQL and NoSQL databases
- Hands-on experience with ETL tools and processes to move and transform data between systems
- Experience with Google Cloud Platform (GCP) is highly preferred.(Experience with other cloud platforms like AWS Azure can be considered.)
- Familiarity with data pipeline scheduling tools like Apache Airflow
- Ability to design build and maintain data pipelines for efficient data flow and processing
- Understanding of data warehousing best practices and experience in organising and cleaning up messy data warehouses
- Proficient in using version control systems like Git
- Experience in a start-up or fast-paced dynamic work environment.
Benefits:
- Competitive Salary: We offer pay that reflects your skills and the value you bring.
- Stocked Kitchen: Enjoy snacks fresh fruit and drinks all day.
- 23 Days Annual Leave: Recharge with 23 days off plus bank holidays.
- Birthday Off: Take an extra day to celebrate your birthday.
- Christmas Shutdown: Relax over the holidays with additional company-wide time off.
- Pet-Friendly Office: Bring your dog to our pet-friendly workspace.
- Team Events: Connect with colleagues through monthly team-building activities.
- Career Growth: Benefit from our focus on internal promotions and development.
- Cycle to Work Scheme: Save on commuting reduce emissions and stay active.
- Expanding Perks: Look forward to more benefits as we grow
Employment Type
Full Time
