Curve

Senior Data Engineer

London, UK
Kafka Go Terraform Python SQL AWS Spark Streaming GCP Machine Learning
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Description


Curve was founded with a rebellious spirit, and a lofty vision; to truly simplify your finances, so you can focus on what matters most in life.


That’s why Curve puts your finances simply at your fingertips, so you can make smart choices on how to spend, send, see and save your money. We help you control your financial life, so you can go out and live the life you want to live.


With Curve you can spend from all your accounts, track spend behaviour and provide insights, and security to protect you from fraud. For the first time giving you bright insights and control of all your money in one beautiful place.


We’re developing a ground-breaking product with our customers at the core. Our user base is growing rapidly and we have exceptional metrics. We have funding from the leading names in tech investment, and a visionary leadership team who wants everyone who joins this remarkable adventure, to have the autonomy to masterfully develop their expertise.


Welcome to Curve. On a mission to help you live inspired.


We’re looking for a capable Senior Data Engineer, who will be part of the data platform team. Our mission is to build a robust platform to collect data from multiple data sources, both internal and external as well as enable reverse-ETL. Using a combination of batch and real-time streaming technologies, the role will facilitate cutting-edge analytics, real-time decisioning, and robust reporting. We believe in data being at the core of the business. We hate latency, approximation and bad data quality!


This role is a great opportunity for people who love data, software architecture, streaming technologies, distributed systems and who want to have a real-world impact by building production systems from scratch with a world class team.


Key Accountabilities:

  • Managing and administering our Data Warehouse to guarantee continuous and high availability of the data.
  • You will mainly be working with GCP (Cloud Storage, BigQuery, Composer, Dataproc, Dataflow), Confluent for Kafka and Snowplow
  • Working with the extended team to understand their needs and translating them into fantastic data products, this includes working with and alongside Machine Learning researchers and data scientists on cutting edge ML models.
  • Designing and building pipelines to collect data from various data sources
  • Data modelling using DBT on top of BigQuery
  • Working with backend, frontend, Devops & QA engineers to ensure that data events are well-designed and correctly integrated to data pipeline services.
  • Helping us implement a data-driven mindset in the company.


Skills & Experience:

  • At least 3+ years’ experience as a data engineer especially using realtime & batch data in a production environment using streaming technologies such as Kafka/PubSub/Kinesis.
  • Understanding of Data Warehousing principles (including indexing, query graphs, basic administration, relational models, etc)
  • You have a proven track record with a programming language. We are especially keen on any or all of the following Python, Go and SQL, specifically in connection with Airflow and DBT respectively.
  • Experience designing and building production systems on GCP and/or AWS infrastructure.
  • Understanding and/or experience of working within Event Driven Architectures
  • Experience deploying and maintaining both batch and real-time machine learning models.
  • Experience using distributed systems at scale in a production environment using technologies such as Spark/Beam.
  • Strong understanding of data quality principles
  • A record of learning new technologies and tools 
  • You are experienced with database technologies. (Best Practice, Performance Optimisation, Fault Finding)


Nice to haves:

  • An understanding or experience of developing Machine Learning solutions.
  • Experience with Terraform/K8’s
  • Have mentored/supported team members.
  • Understand distributed systems and architecture for scale.
  • Understand Security and InfoSec pain points in Data engineering.
  • Fintech/Finance/Payments/Retail Banking experience


Benefits:

  • 25 days plus bank holidays
  • Bonus days off for Learning & Development, Mental Wellbeing, Birthday, Moving House & Christmas
  • Working abroad policy (up to 60 calendar days per year)
  • Bupa Health Insurance (YuLife)
  • Life insurance powered by AIG (5x Annual Salary)
  • Pension Scheme powered by “People’s Pension” (4% Matched)
  • EAP (Mental health & wellbeing support, Life coach, Career coach)
  • 24/7 GP access (Smart Health via YuLife)
  • Annual subscriptions to Meditopia & FIIT for your mind and body (via YuLife)
  • Discounted shopping vouchers (via YuLife)
  • Enhanced parental leave
  • Ride to work scheme & Season ticket loan
  • Electric car scheme
  • Six nights of Night Nanny for new parents
  • Free Curve Metal subscription for you and your +1
Curve
Curve
Apps Banking Financial Services FinTech Payments

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