Data Platform Engineer

About the role

We are looking for a strong Data Platform Engineer to help design, build, and scale the data infrastructure behind our forecasting, analytics, and machine learning products.

In this role, you will work at the intersection of data engineering, cloud infrastructure, DevOps, and machine learning operations. You will be responsible for building reliable data pipelines, improving our data warehouse and lakehouse architecture.

This is a hands-on engineering role for someone who enjoys building robust systems, improving developer workflows, and making data accessible, reliable, and scalable.

Responsibilities

• You will be responsible for:
• Designing, building, and maintaining scalable data pipelines product features
• Developing and optimizing data models using SQL and dbt
• Building data processing workflows in Python using Apache Arrow, Parquet, Polars, pandas, and Duck
• DBDesigning and improving DevOps practices for data science, including testing, CI/CD, deployment, monitoring, and observability
• Setting up and maintaining data pipeline orchestration with Airflow, Dagster, or AWS Step Functions
• Collaborating with product, engineering, and data science teams to translate business requirements into scalable data solutions
• Improving data quality
• Must-have experience
• SQLdbt for data transformation, modelling, testing, and documentation
• Columnar data warehouses, especially Amazon Redshift
• Columnar data processing in Python, including experience with Apache Arrow, Parquet, Polars, or pandas
• Designing DevOps practices for data engineering teams
• Data pipeline orchestration using tools such as Airflow, Dagster, AWS Step Functions, or similar
• Building reliable, maintainable, and production-grade data systems
• Nice-to-have experience
• Arrow Flight SQLCloud and infrastructure-as-codeMLOps and machine learning model monitoring
• Data lakehouse architecture
• Hands-on experience with Dagster
• Feature store architecture
• Airbyte or Fivetran
• Training and deploying machine learning models in production

What we are looking for

This is usually the part where companies insert AI slop about mindset, environment, growth, and other buzzword - but we respect your time so, long story short, we're looking for a person who:

Delivers quality  - but understands that being pragmatic is sometimes necessary ;-)Can communicate effectively with people at any level of expertiseKnows how to build a scalable infrastructure and how to maintain itIf at least 66 percent of the above sounds like a match, come talk to us.