Senior Data Engineer / Data Architect – Azure Data Explorer, IoT streaming (Freelance)

Technologies we use

Expected

• Azure Data Explorer
• KQL
• Python
• Terraform

Optional

• PostgreSQL
• PostGIS
• TypeScript
• NestJS

About the project

We connect talented freelancers with cutting-edge projects, offering a platform for you to showcase your expertise and thrive in a collaborative environment.

Currently we are looking for a Senior Data Engineer with architect skills to join an environmental monitoring platform for industry. You'll take over a working proof of concept of a streaming IoT measurement pipeline on Azure and bring it to production – from edge devices, through the raw layer, to read-optimised data and rollups in Azure Data Explorer.

📍 Location: Remote/Warsaw Office

Start: November

This is how we organize our work

This is how we work

• in house
• you have influence on the choice of tools and technologies
• you have influence on the technological solutions applied
• you have influence on the product
• agile

Your responsibilities

• Take over the PoC and bring it to production – the data semantics are already defined, so you can focus on the pipeline.
• Build the stream processor from Event Hubs to Azure Data Explorer.
• Design and schedule the cascade of rollups and time-window aggregations (raw/Bronze → Silver → aggregates).
• Implement reprocessing of data after configuration changes.
• Model and optimise ADX tables, update policies, materialized views, retention policies and queries for large data volumes.
• Work closely with our PM, our ADX specialist, the client's engineering team and our DevOps.

Our requirements

Must-have:

• At least 2–3 data pipeline projects taken from zero to production in the role of architect or lead data engineer, with Azure Data Explorer in production in at least one of them.

Experience:

• Senior experience in data engineering (around 5+ years), including IoT streams and time-series data

• Broad, hands-on experience with Azure data services

Tech skills:

• Azure Data Explorer (Kusto) and KQL: table modelling, update policies, materialized views, retention policies, query optimisation for large volumes

• Streaming ingestion on Azure: IoT Hub, Event Hubs, parsing functions (e.g. Azure Functions), Blob Storage

• Layered data architecture (raw/Bronze → Silver → aggregates), designing rollups and time-window aggregations

• Python

• Terraform

Soft skills:

• Independence – you can own a production pipeline end to end without hand-holding

• At least B2 in English – we work internationally, so that's a must

• Strong collaboration and communication skills – you'll work with several teams

• Attention to detail

Optional

• Environmental data (spectra, multi-parameter data, interval and event data)

• Preparing data for ML (e.g. anomaly detection) and near-real-time queries

• PostgreSQL/PostGIS and spatial data

• Edge devices / edge computing

• TypeScript/NestJS

This is how we work on a project

• code review
• design patterns
• DDD
• event modeling
• DevOps
• documentation
• issue tracking tools
• functional tests
• integration tests
• regression tests
• testing environments
• unit tests
• manual tests

Development opportunities we offer

• mentoring
• space for experimenting
• technical knowledge exchange within the company
• time for development of your ideas

Benefits

• remote work opportunities
• flexible working time

Recruitment stages

• First call 🤙
• Tech interview 👥
• Offer

How to apply

Along with your CV, please send a short description of 2–3 data pipelines you took to production. For each one: your role, scope, stack, data scale, what went wrong and what you would do differently – plus a link or reference if possible.

STARTUP DEVELOPMENT HOUSE sp. z o.o.

At Startup House we deliver end-to-end AI software for enterprises like Siemens, PwC and Toyota.