Dot Collective

Data Engineer - Azure

Data EngineeringConfirmed live in the last 24 hours

Full-timeWarsaw, PolandNo salary listedIn-person

About the Job

Requirements

Strong SQL and Python skills.
Experience with data modelling, including dimensional, relational, or similar models.
Experience building and maintaining backend systems.
Familiarity with Microsoft Azure.
Understanding of APIs, containers, and backend development best practices.
Ability to implement cloud-native data platforms and engineer scalable, reliable pipelines.
Knowledge of distributed computing with Spark.
Understanding of cloud architecture principles and best practices.
Hands-on experience designing, deploying, and managing cloud resources.
Experience with agile ways of working.
Experience in cloud automation and orchestration using tools such as CloudFormation or Terraform.
Experience monitoring and tuning the performance of cloud-based applications and services.
Knowledge of how to architect, design, develop, deploy, and operate a data platform.

Responsibilities

Develop, maintain, and optimize backend services for the SaaS platform.
Use SQL and Python to build data pipelines and transformations.
Model, structure, and query data to support product features and reporting.
Integrate and maintain data ingestion flows, such as Fivetran and custom connectors.
Implement backend APIs using FastAPI to power the web application.
Work with the cloud environment, primarily Azure.
Collaborate with teammates to plan, build, and deploy features using agile practices.
Contribute to CI/CD workflows, monitoring, and infrastructure-as-code.

Desired Qualifications

Experience with Snowflake, dbt, or CubeJS.
Experience with Databricks, PySpark, or machine-learning workflows.
Experience with containerized deployments using Docker, Kubernetes, or Azure Container Apps.
Frontend development experience with React, Next.js, or TypeScript.
Experience with infrastructure-as-code using Terraform or CloudFormation.
Experience deploying and managing machine-learning models using MLflow, Azure ML, SageMaker, or similar tools, with attention to scalability and performance.
Experience setting up model drift detection, performance monitoring, and automated retraining.
Experience automating end-to-end machine-learning workflows using ML pipelines and CI/CD.
Experience with AWS or GCP is also valuable.

About Dot Collective

We are a new generation consultancy based across UK and EU and founded on the premises of the engineering excellence and empowering people to make an impact.

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:

Strong SQL and Python skills

Data modelling experience (dimensional, relational, or similar)

Experience building and maintaining backend systems

Familiarity with Microsoft Azure

Understanding of APIs, containers, and backend development best practices

Implementing cloud-native data platforms

Engineering scalable and reliable pipelines

Good knowledge of distributed computing with Spark

Understanding of cloud architecture principles and best practices

Hands-on experience in designing, deploying, and managing cloud resources

Agile ways of working

Experience in cloud automation and orchestration using tools such as CloudFormation or Terraform

Monitoring and performance tuning of cloud-based applications and services

Nice to haves: 

Experience with Snowflake, dbt, CubeJS

Experience with Databricks, PySpark, ML workflows

Experience with containerized deployments (Docker, Kubernetes, Azure Container Apps).

Frontend development experience (React, Next.js, TypeScript)

Infrastructure-as-code (Terraform, CloudFormation)

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

Key tasks: 

Develop, maintain, and optimise backend services for our SaaS platform

Work with SQL and Python daily to build robust data pipelines and transformations

Model, structure, and query data to support product features and reporting

Integrate and maintain data ingestion flows (e.g., Fivetran, custom connectors)

Implement backend APIs (FastAPI) to power our web application

Work with our cloud environment (Azure - experience with AWS or GCP also valuable)

Collaborate with teammates to plan, build, and deploy features in an Agile way

Contribute to CI/CD workflows, monitoring, and infrastructure-as-code

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 ability to work on personal projects.

We believe that a geled team is worth its weight in gold – we will do everything we can to avoid breaking well-performing teams. Whilst continuity across every project is not always possible, we thoughtfully assemble high-performing, blended teams with the appropriate levels of experience and expertise to deliver the best outcomes for our clients — and teams you’ll enjoy working with.

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.

About the Company

Dot Collective

Company size: Not listed
Company stage: Not listed
Total funding: Not listed
Headquarters: Not listed
Founded: Not listed

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