Data Engineer - Azure

Dot Collective; Województwo mazowieckie; Hybrid; PLN 180,000 - 280,000; Full time

Benefits offered by this job

Remote-friendly

Wellbeing program

Job summary

Dot Collective is seeking a data & backend engineer to design, build, and optimise data pipelines and backend services for a SaaS platform. You will work daily with SQL, Python, and Azure, shaping data models and APIs to support product features and reporting.

You’ll engage in cloud automation, CI/CD, and infrastructure-as-code while collaborating in Agile teams to deliver scalable, reliable data solutions.

Qualifications

• 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.

Responsibilities

• 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.

Skills

SQL

Python

Data modelling

Azure

APIs & containers

Cloud-native data plat

ETL pipelines

Spark

CI/CD

Infrastructure as code

Monitoring & tuning

Tools

Snowflake

dbt

Databricks

PySpark

ML workflows

MLflow/Azure ML

Terraform/CloudFormation

Docker/Kubernetes

Job description

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.

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.