Senior Data Engineer - MLOps
London or Remote EU
Applications have closed
Meet Cleo.
Looking to do some work that matters?
We get it – it’s why most people come to Cleo. Together we’re fighting for the world’s financial health, building an AI that helps you make the best money decisions from day one. We’ve helped 4 million people so far with personalised insights and a voice you don’t expect in FinTech. But it’s time to do more.
As we enter the next phase, we’re looking for more improvisers, data geeks and grown ups who want to own their work and create meaningful change.
Watch this to dive a little deeper
What you’ll be doing
As one of the first Data Engineers at Cleo you will be solving in broad and interesting challenges. From helping us build the best systems to ingest, transform and store our data to working with Data Science on building out the next generation of platforms and tools to accelerate delivering value to our customers through machine learning.
As Cleo grows rapidly towards 100M worldwide users, the problems we’re trying to solve get more complex. You’ll take the lead in driving improvements to our data platform and data engineering stack to accommodate this growth and provide the best service to our users.
We have a flat and open engineering culture where data and evidence beats opinion and hierarchy. We passionately believe in forming autonomous, cross functional teams who are empowered to deliver our ambitious strategy. You’ll work alongside our engineering team to help us collect, transform, store, and serve data across the company. You’ll also work closely with the data science function here at Cleo; a hotshot team of six dedicated data experts with significant industry experience that are at the heart of everything we do at Cleo.
- Develop and architect our deployment of machine learning in production, with a focus on how we can decrease time to value, improve collaboration and remove manual steps. Think; CI/CD/CT, feature stores etc.
- Building out and owning how we excel at MLOps including both the systems and processes needed to make this successful
- Owning the data infrastructure and architecture, developing best practices to ingest and process data both for ML systems and the wider data team.
- Work with various business and engineering teams to ensure reliable, scalable, robust architecture for our data platform. Work with the engineering team to ensure application design accommodates reporting and analytics requirements.
- Supporting data scientists with automation, tooling, data pipelines and data engineering expertise
About you
Requirements and Nice to Haves
-
- 5+ years of software engineering experience with a focus on data, ideally in Python
- Experience deploying machine learning into production and building systems that optimise this process
- Experience working hand in hand with Data Scientists, mentoring them on best practice and designing systems to make them more effective.
- Experience in DevOps/MLOps. Automation (CircleCI, Jenkins), infrastructure as code (Terraform, CloudFormation)
- Knowledge of real-time systems such as Kinesis or Kafka is a plus!
- Experience with data warehousing solutions such as Snowflake, Redshift, or similar managed solutions
- Experience with ETL tools such as Stitch, AWS Glue, Google Dataflow, or Apache Spark
- Commercial experience working AWS technologies such as SageMaker, EC2, S3, EMR and Redshift
- Experience with data monitoring, observability and threshold alerting tools
- Bias for action. You see a problem, you fix a problem. You get buy-in for your solutions and keep tickets moving. We’re always looking for ways to ship at pace.
What do you get for all your hard work?
- An above market compensation package (Base + Equity). We're prepared to pay for the very best
- Work at one of the fastest growing tech startups anywhere in the world who are backed by top VC firm, Balderton
- The team is exceptional. You'll get to work with brilliantly forward-thinking and dedicated individuals every day
- Our mission is standout. We want to radically improve everyone’s relationship with money. We're not maximising the time consumers spend in a feed, getting fast food delivered, or building an incrementally better bank. We're changing an industry in a visceral way, which you get to see every day in our customer feedback
We are committed to making Cleo a more diverse and inclusive workplace. We are making continuous changes in order to make sure that all voices, especially those of minorities are heard, supported and celebrated. Our work doesn't stop at hiring, and we are providing every employee with training, support and development throughout their Cleo career, alongside training specific to inclusivity.
Tags: AWS CI/CD Dataflow Data pipelines Data Warehousing DevOps EC2 Engineering ETL Excel FinTech Kafka Kinesis Machine Learning MLOps Pipelines Python Redshift SageMaker Snowflake Spark Terraform
Perks/benefits: Career development Equity Flat hierarchy
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