Data Platform Engineer

📢

The job offer is currently closed, but if you're interested and believe you would be a good fit, we encourage you to apply. We'll keep your application in mind for future opportunities.

Engineering culture

🚀
Ship early
and often
📦
Only one project
at a time
🧪
Testing is a first
class problem
🙋🏽‍♂️
Always be
recruiting
📨
Communicate openly and frequently



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Audiense is an equal opportunity employer, and we know it's our differences that makes us great, so we want to welcome people from all backgrounds to our family. We encourage black, brown, LGBTQ+, disabled, mums and dads to apply!

During the application process please feel free to share which pronouns you use (she/her/hers, he/him/his, they/them/theirs). And please let us know if you need any reasonable adjustments for the application or the interview.

The Company

Audiense is an audience intelligence platform that combines rich social data sources with the world’s leading cognitive and machine learning to provide social consumer segmentation and cultural insights. It enables you to understand the audiences that matter to your business better as well as fueling a variety of use cases including buyer personas, social listening, influencer marketing or advertising.We help marketers and consumer researchers identify relevant audiences, provide actionable insights and inform their strategies on how to grow their business.

We’re hiring a senior backend engineer to work in our data platform. Our data platform is the core of our product, and the data we process, curate, and enrich is what allows our customers to identify audiences, extract insights and inform their decisions.

We handle over one thousand million social profiles, enrich, classify and enhance them with the information that allows our customers to define their marketing campaigns, identify influencers and discover new market niches.

You’ll be working in a fully remote, cross-functional team. Ideally, you’ll have experience working with data platform concepts such as datalakes, streaming pipelines (Kafka), ETLs, etc, but if you are a motivated quick learner with experience in even only a few of these concepts you’ll pick things up. We currently write code in Python, Typescript and Scala, however we try not to be locked into one particular technology. We want to find individuals with potential, an interest to grow with us and help us improve.

As the data platform is the core of our product, we are dedicating a lot of effort and research to improving and developing it. Here are some example projects you may work on:

  • Implementing Kafka consumers and producers as part of our recently deployed streaming oriented data pipeline (we have just migrated from batch oriented pipelines to a more real time oriented model with Red Panda at its core).
  • Designing and deploying new enrichment processes to expand our social profiles, from machine learning processes that infer age range to interest identification algorithms (there’s a lot of space for innovation here, and we are constantly looking for new technologies to apply).
  • Creating Airflow DAGs to automate processes and make our lives easier when managing our Datalake.
  • Writing and running Spark jobs to extract insights from our datalake that help us answer our customers’ questions.
  • Finding ways to optimise our query engine, enabling our customers to find better, more specific audiences.

Generally speaking, we’re after individuals that understand the potential of the data we handle, are eager to learn as well as to teach, help us grow and feel comfortable exploring the possibilities of our product.

You’ll probably have at least 3-4 years’ experience working in the backend engineering field. Having said that, we are more interested in what you have done than how long you have been doing it. We’d love to hear about some of the projects you have been working on that could resonate with what we do: How it was built and how you took part in its success.

Our mindset, workflows and communication assume that we are all remote. Almost everything is documented in Notion and/or Github: from our Product Engineering Principles to our Apprentice Program: Growth plans, learning path, architecture, protocols, onboarding, playbooks, design system, UX guidelines, etc. We are fully committed to automating our daily routines so we can work efficiently whilst remote and be as autonomous as possible.

You will be joining a cohesive team (with an average of 4 years of experience together) in a very collaborative environment in which you will feel cared for from the start of your onboarding.

We believe in extreme programming as a development technique so most of the time we do pair programming (yes, remotely) and TDD is our main tool for writing robust and testable code. Pair programming always helps us trust our code allowing for constant iterations. Once per sprint we spend time on joint code review to detect possible glitches to prioritise. We do continuous integration, and try to apply trunk base development in most of our projects.

We expect you to align with our values and way of working, but we also value your input and are open to suggestions for improvement. We have dedicated a lot of effort in declaring our Product Engineering Principles and try to always keep them in mind in our every day decisions.

Salary and Benefits

We are offering anywhere between 40k-55k€ depending on experience and impact. We also offer several other benefits including:

How to apply

Send an email to jobdev@audiense.com introducing yourself and telling us why you fit the profile we are looking for. Your CV will also be useful but it is not the most important.

If you pass the initial application filtering, or we contact you directly, your first interview will be with the data platform team lead (Javier Baena).

You’ll have a second interview with some members of the team. This is a great opportunity to ask your future teammates any questions you may have.

Then we would look for a way to validate your skills and experiences. The best way to accomplish this is by pair programming with our team on real tasks. The more time we spend pairing, the more we can both validate if we like each other and especially if you like our way of working, the challenges and the team. Of course, we would pay for your time. If this approach doesn’t work for you, we would try to offer other alternatives.

Lastly you will have a quick talk with Alfredo Artiles, our CTO in which you can ask any final question you may have.

If you decide to join our team, this will be the ideal onboarding:

As our development flow is adapted to pair programming your contribution will be very progressive, and you will always have someone to revert to with any questions you may have.

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