Senior Data Engineer

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📅  Posted 14 days ago 📍 United Kingdom
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Job Description

Who is Current Health?

Current Health is a leader in the movement to transition more healthcare into the home. We’re a technology company, but beyond our best-in-class hardware and software capabilities, we help healthcare organisations operationalise care at home and deliver excellent patient experiences through helping with the last mile of care logistics and services. We partner with leading healthcare organisations to advance home-based care in the US, the UK, and around the world.

More than doubling in size in the last year, we’re building a global team united in one purpose: helping people live healthier, longer lives by predicting disease and enabling earlier treatment. At Current Health, we seek to put patients first, solve problems with curiosity and creativity, pursue uncommon collaboration, and never stop growing. We’re a remote-first company, which means that everything from how we work, communicate, and socialise is shaped by tools and culture that prioritise collaboration and support independence.

What does a Data Engineer at Current Health do?

We are in the process of revamping our patient admissions/enrollment capabilities - we’d like to introduce support for net new fields captured within that process, as well as define the most appropriate locations for that data to be stored so that it can be used within different workflows of the future. As a specialist in data engineering, you will help us throughout the process by assisting software engineers and drive the project from a data perspective.

As well as helping support our services across our software platform and applications, you will also help support and evolve our existing data products and provide analytical support to external clients and Current Health teams.

You will also be working closely with the data team who are building a new data platform whereby we will make all our data accessible in one place and build data products that use this data thus allowing our engineers, data scientists, bio-medical engineers, and clinical researchers to perform analytics which will help us to drive patient engagement, clinical impact, and client growth.

How we work as a team

We would describe ourselves as self-organising and collaborative with a continuous improvement mindset. We value knowledge sharing and making decisions as a team, regardless of role or level of seniority. We encourage collaboration via e.g.pair programming and holding regular knowledge share sessions. We seek to continuously improve as a team, and we also look to support each other's growth.


  • Salary Exchange Pension scheme (5% employee, 3% employer contribution)
  • Private Medical Insurance through Vitality
  • Competitive bonus scheme
  • 2 x Life Assurance cover
  • Critical Illness cover
  • Employee Assistance Program
  • £10 pcm flex pot to use toward benefits in our Benni benefits portal
  • On call allowance (Only payable if and for so long as you provide on call services)
  • Flexible, autonomous working environment
  • Bike to work scheme
  • Give as you earn through payroll

We want to hear from you if…

You meet some or many of the points below. This is some of the experience we would be looking for to help you be successful in our team:

  • Experience in real-time stream or batch processing.
  • Designing and implementing systems with scale in mind.
  • Deep knowledge of at least one modern programming language (we use Python and Java).
  • Proficiency in data manipulation using e.g. SQL, Spark, pandas or similar.
  • An eagerness to learn new languages and technologies as required.
  • Writing code with a focus on testability.
  • Be confident reviewing and troubleshooting code.
  • Have implemented solutions in a cloud computing and networking environment (we use AWS along with terraform/IaC).
  • Collaborating outside your own team. We work closely with data engineers, product teams and other consumers of data products.

Technologies we use

  • Querying and analytics: Python, SQL, dbt, Databricks, AWS Athena, AWS Glue
  • Orchestration: Airflow
  • Storage: PostgreSQL(RDS), Redshift, DynamoDB, AWS S3
  • Monitoring: DataDog, CloudWatch