Senior Data Engineer / DataOps

You’ll play a key role in developing our ML & Data platform from ground up, as part of a small, high-performing team. You will influence the scope and technical direction as well as champion best practices within the team. You will continuously pursue clean code practices and contribute towards overall platform architecture, collaborating with our other Engineering and Product teams.

You will:

Work with engineers, researchers and data scientists to build the next generation of Tractable’s ML & Data platform
Help identify and realise capabilities in our ML & Data platform that massively speed up getting research to production across dataset & model management, model training, model serving, labelling, Data & ML pipeline orchestration and more
Support Research and Product Engineers with tools and processes to enable a seamless data flywheel
Deploy and continuously develop robust infrastructure, using best practices for managing infrastructure-as-code
Solve cost and performance scalability challenges in both model training and model serving
Run, monitor and maintain business-critical, production systems
Adopt open-source technologies to best leverage our in-house resources
Promote engineering best practices throughout the team
Suggest, collect and synthesise requirements to create an effective feature roadmap
Tech Stack:

We rely heavily on the following tools and technologies, but we are likely to explore new technologies / frameworks as we are building the platform from ground up. You don’t need to have prior experience in all of them, and we actively encourage diverse views on what the best tools for the job are. We’re just keen to know that you’re willing to break things, fix things, learn fast and help build a great team that is capable of building a platform that delights our customers.

Main Infrastructure: AWS (EC2, S3, MSK, Lambda, StepFunctions, Glue, IAM, Cognito, Systems Manager, CloudWatch, SQS, Route 53, Sagemaker), Apache Kafka (AWS MSK), Kubernetes, Datadog (Metrics, Logs, Synthetics), Pagerduty
Main CI/CD: Terraform, Docker, Harness
Main Databases: Postgres / RDS, Redis, DynamoDB
Main Languages: Python, Node + Typescript, SQL (Postgres)
Main Data stack: AWS MSK, AWS Lambda, AWS Redshift, dbt, Airflow, Airbyte, AWS Glue
Main ML stack:  Triton, TFServing, KServe, AWS Sagemaker, AWS Lambda, AWS MSK, sync/async APIs, Weights & Biases, Tensorflow, Pytorch, dvc, Dagster/Flyte, Streamlit
We encourage you to drop us a line even if you don’t have all the points above. That’s a lot of different areas of responsibility! We will help you pick them up because we believe that great people come from all walks of life.

What you need to be successful:

A strong Data Engineer, who is passionate about building platforms that massively reduce lead time from bringing Machine Learning research to production. You have a solid background in core software engineering principles, are happy deploying & managing infrastructure, and have a good understanding of the difficulties faced by data scientists. A few things we are particularly interested in seeing from you:

Great communication skills and a collaborative mindset
An ability to independently catalyse both process and technical change in a complex, highly cross-functional environment
2+ years of experience building and/or managing scalable data infrastructure (data ingestion, data lake, data warehouse, data orchestration), ideally on behalf of other users within an organisation
Worked with Python in a professional environment for 2+ years
Experience in building robust data pipelines
Experience deploying and managing infrastructure-as-code, preferably via Terraform or AWS CDK
Able to design scalable, robust, fault-tolerant, cost-effective system architectures and compare trade-offs (distributed systems experience a plus)
Experience building robust, intuitive tooling to support internal users (e.g. common libraries, CLIs etc.)
Cares about team practices / pairing / advocate of CI/CD
Understanding of core ML concepts, with experience in supporting data scientists and researchers across the full Model & Data lifecycle

What’s in it for you

Generous financial reward for your effort

Yearly compensation reviews
Generous equity package
5% employer match on pension

Time off and flexible working

25 days paid annual leave + bank holidays
Ability to work from abroad for up to 6 weeks/year
Competitive maternity + paternity leave
Flexible hours and hybrid working 
Additional leave to support you when you need it, including sick pay, compassionate leave, or paid time-off to recharge after an intense work period.

Support for your health and wellbeing

Highest tier of private health coverage through Bupa 
Eyewear and eyetests expense scheme
Annual Headspace Subscription
Mental health coaching with Sanctus

Additional perks 

Workplace Nursery Benefit
L&D budget to use on Learnerbly (our learning platform)
WFH expense scheme
Cycle to Work scheme
Charity donation scheme with Tyve

Diversity commitment

At Tractable, we are committed to building a diverse team and inclusive workplace where people’s varied backgrounds and experiences are valued and recognised. 

We encourage applications from candidates of all backgrounds and offer equal opportunities without discrimination.

#LI-HM1

Diversity commitment

At Tractable, we are committed to building a diverse team and inclusive workplace where people’s varied backgrounds and experiences are valued and recognised. 

We encourage applications from candidates of all backgrounds and offer equal opportunities without discrimination.