Data Engineer

February 15

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SuperAwesome

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SuperAwesome powers safe, authentic digital engagement with Gen Alpha and Gen Z. SuperAwesome’s technology is used by hundreds of brands and content-owners to safely engage with over 500M young people from Gen Alpha and Gen Z every month. The company's DNA of privacy, curation, and moderation helps keep Gen Alpha safe online, and enables brands to connect with Gen Z’s values of privacy, inclusive communities, and authentic content. SuperAwesome has reshaped the digital media landscape for young people with their tools and technology, including their AwesomeAds Marketplace (certified under the FTC's COPPA Safe Harbor programs and GDPR), SuperAwesome Creators (brand-safe influencer marketing), and Kids Web Services (parent verification).SuperAwesome was recently named the 8th fastest growing private technology company in Britain (The Sunday Times Tech Track 100 2017) as well as one of Europe’s fastest growing companies (Financial Times 1000: Europe’s fastest growing companies). The company was awarded a Breakthrough Technology Award at the Campaign Creative Tech Awards 2017 for REX, the world’s first kid-safe programmatic ad filter. In 2023, SuperAwesome won a Bronze Cannes Lion in Brand Integration for Games for its work with Frank's RedHot and was named one of the Top 3 Most Effective Independent Agencies by the Effie Awards. We have offices in London, New York, Los Angeles, Chicago, Singapore and Sydney. For more information, please visit us at www.superawesome.com Instagram (@gosuperawesome) or Twitter (@GoSuperAwesome). For more information on our jobs, please visit us at https://www.superawesome.com/careers. Möchten Sie sich unsere deutsche Website ansehen? Klicken Sie hier: https://www.superawesome.com/superawesome-de/

Marketing & Advertising • Kids Media & Discovery Platform • Kids and Teens Market Research & Insight • Design & Development • AdTech

51 - 200 employees

📋 Description

• Our teams are growing rapidly and we’re hiring a Data Engineer to take our products to the next level of scale. • Use your experience in data engineering to help define Data as a Product, and bring your expertise to improve not just the product itself but the client experience, leveraging data, from ETL to the presentation layer. • You will work closely with your Tech Lead and the other engineers in your team to define the appropriate technical approach, metrics, and timelines. • You will have your say in the product roadmap and help the team and the Product Manager to make the most informed decisions to break down complex tech deliverables into simple and understandable user stories. • You will drive collaboration, gather feedback, solve problems, and tackle challenges through tests and learning. • Quality is key for us, so you will ensure all product components are built to an appropriate level of quality for the stage (alpha/beta/production), deliver products using the appropriate level of testing and monitoring, fail fast, and learn and iterate frequently. • You will champion continuous improvement and always aim to improve the product your team owns and measure your impact with the appropriate tech, product, or delivery metrics. • In this role you will: • work across the full stack depending on where you can drive the highest impact: from ETL pipelines to data warehousing to visualisations, as well as testing and cloud infrastructure. • work with your team to design and implement features and services for the data analytics solution, and keep the design choices well-documented and explained. • train/mentor other Data engineers on Data engineering best practices. • use your experience to create/improve predictive data quality. • champion the DataOps culture, support data systems in production, including participation in our out-of-hours on-call rota. • communicate with customers to discuss new use cases or help them identify and fix data issues, as well as manage the end-to-end setup for them: from raw data analysis, to defining and implementing data ingestion/enrichment pipelines to creating data visualisations.

🎯 Requirements

• Good understanding of Data pipeline design and implementation using Databricks, and Python (or Python derivative, like PySpark) • Good visualization skills using Sisense and/or other visualisation tools • Good experience with SQL • Good understanding of Data management and/or Data governance (making sure the data is of expected volume, schema, etc.) • Nice to have: • Good understanding of microservices architecture principles • Experience with Kedro on Databricks • Exposure to AWS or other cloud provider • Exposure to Airbyte reading from multiple different data sources