Senior Data Engineer

Partnerize
London
11 months ago
Create job alert

Who We Are:

The partnership channel offers scale and automation on a pay-for-performance model that delivers the operating leverage necessary for brand survival. Partnerize empowers marketers with technology built to discover, engage, and convert audiences, at scale, all while maintaining brand safety and control.

Why Join Us?

Our commitment to growing partnerships doesn't end with our clients. Our employees are carefully selected to be a part of our company because they emulate a carefully crafted and practiced set of core values that define us and our business. Joining Partnerize means joining a company that sincerely values your talent, expertise, and passion. We strive each day to hire and retain only the best. Doing so affords us the opportunity to be the best in the business, to exceed our clients' expectations, to innovate, to teach—and most importantly—to earn and maintain our clients’ loyalty.

The things you care about

At the heart of our platform, we track performance marketing data and build solutions to turn this data into useful information for our customers. We work with a lot of data, generating over a billion events across our infrastructure daily. We aim to make as much of this data available in real-time as possible, which is no mean feat at this scale!

We are looking for a highly skilled Senior Data Engineer to join our team. The ideal candidate should have extensive experience with Google Cloud Platform, Google BigQuery, Apache Airflow, Airbyte, HDFS, Apache Spark, and Hive.

As a Senior Data Engineer at Partnerize, you will:

Design, build, and maintain data pipelines using Google Cloud Platform, Google BigQuery, Apache Airflow, Airbyte, HDFS, Kafka and Apache Spark Integrate large sets of data from numerous internal and external sources Ensure the reliability and performance of data systems by implementing best practices for data quality, security, and scalability Collaborate with cross-functional teams to understand business objectives and translate them into technical solutions Collaborate with data scientists and other stakeholders to support data-driven decision making and implement data solutions Design and implement data models and explain trade-offs of different modeling approaches Stay up to date with the latest developments and technologies in the data engineering field

You are a data engineer with:

Strong experience with Google Cloud Platform, Google BigQuery, Apache Airflow, Airbyte, HDFS, and Apache Spark Experience with data warehousing, data modeling, and ETL data pipelines design, implementation, and maintenance Good knowledge of software engineering practices and hands-on experience with writing Python production-level code Good knowledge of SQL and approaches to query optimization Strong understanding of data security and privacy principles Excellent problem-solving and critical thinking skills Strong communication and collaboration skills

We hope you have:

Good understanding of CI/CD Experience of working in an Agile environment and understanding of key agile practices Experience with data management for BI tools like Tableau

UK Benefits & Perks

25 days holiday in addition to bank holidays  Enhanced Parental Leave: 6 months full pay for birth parent, 4 weeks non-birth parent at full pay after one year employment 5 extra 'Partnerize Parental Days' each year Private Medical Insurance through Bupa  Enhanced pension contributions Cycle to Work scheme  Eye Care Vouchers  Life Assurance Enhanced Wellness Program including access to EAP, Wellness Coaching & Wellness Fridays program Regular company events and activities

Related Jobs

View all jobs

Senior Data Engineer

Senior Data Engineer

Senior Data Engineer

Senior Data Engineer - Snowflake & AWS

Senior Data Engineer

Senior Data Engineer

Get the latest insights and jobs direct. Sign up for our newsletter.

By subscribing you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

AI Jobs for Non‑Technical Professionals: Where Do You Fit In?

Your Seat at the AI Table Artificial Intelligence (AI) has left the lab and entered boardrooms, high‑street banks, hospitals and marketing agencies across the United Kingdom. Yet a stubborn myth lingers: “AI careers are only for coders and PhDs.” If you can’t write TensorFlow, surely you have no place in the conversation—right? Wrong. According to PwC’s UK AI Jobs Barometer 2024, vacancies mentioning AI rose 61 % year‑on‑year, but only 35 % of those adverts required advanced programming skills (pwc.co.uk). The Department for Culture, Media & Sport (DCMS) likewise reports that Britain’s fastest‑growing AI employers are “actively recruiting non‑technical talent to scale responsibly” (gov.uk). Put simply, the nation needs communicators, strategists, ethicists, marketers and project leaders every bit as urgently as it needs machine‑learning engineers. This 2,500‑word guide shows where you fit in—and how to land an AI role without touching a line of Python.

ElevenLabs AI Jobs in 2025: Your Complete UK Guide to Crafting Human‑Level Voice Technology

"Make any voice sound infinitely human." That tagline catapulted ElevenLabs from hack‑day prototype to unicorn‑status voice‑AI platform in under three years. The London‑ and New York‑based start‑up’s text‑to‑speech, dubbing and voice‑cloning APIs now serve publishers, film studios, ed‑tech giants and accessibility apps across 45 languages. After an $80 m Series B round in January 2024—which pushed valuation above $1 bn—ElevenLabs is scaling fast, doubling revenue every quarter and hiring aggressively. If you’re an ML engineer who dreams in spectrograms, an audio‑DSP wizard or a product storyteller who can translate jargon into creative workflows, this guide explains how to land an ElevenLabs AI job in 2025.

AI vs. Data Science vs. Machine Learning Jobs: Which Path Should You Choose?

In recent years, the fields of Artificial Intelligence (AI), Data Science, and Machine Learning (ML) have experienced explosive growth. Spurred by the increase in data availability, advances in computing power, and the demand for intelligent decision-making, organisations of all sizes are investing heavily in these areas. If you’ve been exploring AI jobs on www.artificialintelligencejobs.co.uk, you’ve likely noticed that employers use terms like “AI,” “Data Science,” and “Machine Learning”—often interchangeably. While they are closely related, there are nuanced differences between these fields. Understanding these distinctions is key if you’re trying to decide which path suits you best. This comprehensive guide will help you differentiate among AI, Data Science, and Machine Learning. We will discuss the key skills for each, typical job roles, salary ranges, and provide real-world examples of professionals working in these fields. By the end, you should have a clearer idea of where your strengths and passions might fit, helping you take the next step towards securing your ideal role in the world of data-driven innovation.