Senior Data Engineer Data Analytics · Porto, Portugal · Fully Remote
2 semanas atrás
An innovative B2B MaaS (Manufacturing as a Service) platform and Artificial Intelligence (AI) powered system that connect buyers and sellers with unprecedented efficiency.
Conventional manufacturing is infamously challenging for companies both big and small.We're tackling that head on by making reliable manufacturing methods instantly available to engineers all over the world through our digital platform.
Empowering every one of our customers to create revolutionary products faster, Geomiq democratises access to transparent & predictable manufacturing.If you're looking for a B2B tech scale-up selling into some of the world's leading brands from BMW, Rolls Royce to Brompton Bikes & Google look no further (we have even supported space missions)
We are Manufacturing the Future
About the Team A London-based tech start-up and a team of entrepreneurs with a proven track record. We are solving our own problem (one that we faced every day as engineers) of how difficult it is to order custom manufactured parts via conventional manufacturing, we are on a mission
Our culture is friendly but incredibly fast paced – we are constantly challenging, testing and adapting the way we do things.
We're also really committed to working with integrity, doing the right thing, and building a company we are truly proud of.
We're growing super-fast but we also want to make sure that we are building a company on really solid foundations.
Our Product A revolutionary platform that completely digitises the existing process of quoting and ordering of custom manufactured parts whilst ensuring the highest operational and quality outcomes.
Our main customers are Design Engineers, Mechanical Engineers and Procurement teams building the world's most innovative products.Check out the platform here:
, and view a video of the 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.
You'll be responsible for collecting data from various sources, ensuring its structure, and making it easily accessible for Business Intelligence and Data Science purposes.
Key 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.
What are we looking for? Experience Required:
Bachelor's degree in Computer Science, Engineering, or a related field (or equivalent experience) 3-5 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 Stocked Kitchen of snacks, fruit etc 23 days annual leave, not including bank holidays Extra day off for your birthday Monthly Team events Culture of internal progression Cycle to work scheme More to come as we grow#J-18808-Ljbffr
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