Data Engineer

🕒 July 30

🇵🇹 Portugal – Remote

⏰ Full Time

🟡 Mid-level

🟠 Senior

🚰 Data Engineer

👻 Ghost score 24%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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SuperAwesome

WebsiteLinkedInAll Job Openings

51 - 200 employees

📣 Marketing

Marketing

SuperAwesome is a technology company that powers safe and authentic digital engagement for Gen Alpha and Gen Z. Its technology is utilized by numerous brands and content owners to engage with over 500 million young users monthly. Known for its emphasis on privacy, curation, and moderation, SuperAwesome provides tools that ensure digital safety for young audiences while enabling brands to connect with their values. Their offerings include the AwesomeAds Marketplace for compliant advertising, SuperAwesome Creators for brand-safe influencer marketing, and Kids Web Services for parent verification. The company has earned various accolades for its innovative approach in the digital media landscape for youth, including recognition as one of Britain's fastest-growing private technology companies and awards at prestigious events like the Cannes Lions.

📋 Description

• Define Data as a Product and improve the product and client experience across ETL through the presentation layer • Work closely with the Tech Lead and engineers to define technical approaches, metrics, and timelines • Contribute to the product roadmap and help break down complex technical deliverables into user stories • Drive collaboration, gather feedback, solve problems, and tackle challenges through testing and learning • Ensure product components meet appropriate quality standards for alpha, beta, and production stages • Deliver products with appropriate testing and monitoring • Champion continuous improvement and measure impact with technical, product, or delivery metrics • Work across the full stack, including ETL pipelines, data warehousing, visualisations, testing, and cloud infrastructure • Design and implement features and services for the data analytics solution and document design choices • Train and mentor other Data Engineers on Data Engineering best practices • Create or improve predictive data quality • Champion DataOps culture and support production data systems, including participation in the out-of-hours on-call rota • Communicate with customers about use cases and data issues • Manage end-to-end customer setup, from raw data analysis and ingestion/enrichment pipelines to 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 • 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