Data Engineer

The Dot Collective; London; On-site; GBP 40,000 - 80,000; Full time

Job summary

An innovative consultancy is seeking passionate individuals who can leverage data's transformative power. This role involves implementing cloud-native data platforms and engineering scalable pipelines, allowing you to make a significant impact in a short time. You'll work in a supportive environment that prioritizes employee wellbeing, with flexible working arrangements and a strong focus on collaboration. If you're excited about modern tech stacks and agile methodologies, this is a fantastic opportunity to thrive in a dynamic team where your contributions will be valued and recognized.

Benefits

Comprehensive employee wellbeing program

Mental health support

Flexible working arrangements

Wellness activities

Sabbaticals

Parental leave

Co-working spaces

Personal project time

Qualifications

• Experience in implementing cloud-native data platforms and engineering pipelines.
• Strong skills in Python and SQL, with knowledge of distributed computing.

Responsibilities

• Design, deploy, and manage cloud resources for data platforms.
• Monitor and tune cloud-based applications for performance.

Skills

Cloud-native data platforms

Scalable and reliable pipelines

Distributed computing with Spark

Cloud architecture principles

Cloud resource management

Python

SQL

Agile methodologies

Cloud automation and orchestration

Tools

CloudFormation

Terraform

MLflow

Azure ML

SageMaker

Job description

About The Dot Collective

We are a new generation consultancy based across UK and EU and founded on the premises of engineering excellence and empowering people to make an impact. All our consultants have equity in the company, genuinely love what they do, and are really good at it.

We work with all modern tech stacks and typically run agile scrum on all our projects.

About you

Are you passionate about data and its transformational powers? Do you like being able to make a huge difference in a limited period of time? We might be just the right place for you.

Your key skills and capabilities:

1. Implementing cloud-native data platforms
2. Engineering scalable and reliable pipelines
3. Good knowledge of distributed computing with Spark
4. Understanding of cloud architecture principles and best practices
5. Hands-on experience in designing, deploying, and managing cloud resources
6. Excellent Python and SQL skills
7. Agile ways of working
8. Experience in cloud automation and orchestration using tools such as CloudFormation or Terraform
9. Monitoring and performance tuning of cloud-based applications and services

Nice to haves: (MLOps):

• Model Deployment & Serving - Deploy and manage ML models using MLflow, Azure ML, SageMaker, or similar, ensuring scalability and performance.
• Monitoring & Retraining - Set up model drift detection, performance monitoring, and automated retraining.
• ML Pipelines & CI/CD - Automate end-to-end ML workflows.

We expect you to have some knowledge about how to architect, design, develop, deploy, and operate a data platform.

Our promise to you

We will always see you as a human being and will do our very best to support your needs and wellbeing - well-designed co-working and collaboration spaces, remote working patterns that work for you, parenting leave, sabbaticals, and the ability to work on personal projects.

We believe that a gelled team is worth its weight in gold - we will do everything we can to avoid breaking well-performing teams - your team will be stable across different projects and you will work with people you trust and like.

We are committed to prioritising the wellbeing of our employees. To fulfill this promise, we provide a comprehensive employee wellbeing program that includes mental health support, flexible working arrangements, wellness activities, and a positive work culture.

We recognise that the world of tech delivery has moved on significantly in the last 15 years and know a thing or two about how to bring projects over the line without experiencing lots of despair and burn-out. In fact, we like to believe that our projects are the opposite of that - they are run smoothly and most of the time are fun to work on.