The Role

As a Senior Data Engineer on the Data Team, you'll continue to build and and improve the data platform the whole company relies on. Data at Gigs cuts across everything: usage events from telecom networks, billing and revenue data, product analytics, and the numbers Finance closes the books with.

We build data systems to solve business problems, not for their own sake. You'll make pragmatic technical decisions based on what the business needs, balancing speed, correctness, and long-term maintainability.

You care deeply about data modeling and how data is consumed, not only how it's moved and stored. As a senior engineer, you'll set architectural patterns and standards, and you'll make decisions the team builds on as it scales.

It's a cross-functional role. You'll work closely with Finance, Network Integration, Product, and other teams to understand their problems and turn them into reliable data products. You'll join a small Data Team reporting to our Head of Data, with a big surface area and significant influence over the technical direction of data at Gigs.

Salary range for Senior Data Engineer:

EU: €90,000-125,000
UK: £90,000-125,000

(The final offer depends on your background, skills, and how you perform through the process.)

What You Will Do

Build systems that turn complex usage and operational data into trustworthy datasets used for billing, financial reporting, and product decisions.
Build and operate the data platform and pipelines that power these use cases.
Integrate data from across the business — internal systems, third-party tools, and external partners — into one consistent platform.
Own data model ing across the warehouse and set standards for how data is structured as we scale.
Work mostly in Python and SQL, with Dagster as our orchestrator.
Build and maintain the cloud infrastructure behind the platform, managed with Terraform.
Work directly with stakeholders. Understand their problem, then deliver data they can trust.
Design for correctness and observability. Build the tests, monitoring, and data quality checks that make our numbers reliable.
Take problems from scoping to production, and operate what you build.

You can find more about how we work on our engineering page.

What We Are Looking For

You've designed and operated production data platforms. You've made architectural decisions around ingestion, storage, modeling, orchestration, and reliability, and you understand the trade-offs between them.
You have strong data modeling fundamentals. You have well-developed views on how data should be structured, can explain the trade-offs behind them, and know when different approaches make sense.
You put business value first. You build for impact, not for the sake of building, and you know how to make pragmatic trade-offs between speed and quality.
You're comfortable working with ambiguity. You can take an underspecified problem, work out what matters, and drive it to a production solution.
You use AI tools effectively as part of your engineering workflow. You give agents good context, critically review their output, recognize when they're wrong, and stay accountable for the code and technical decisions that result.
You're strong in Python and SQL, and experienced with modern cloud data platforms such as BigQuery, Snowflake, or Databricks.
You've worked with data orchestration tools such as Dagster, Airflow, or Prefect. We use Dagster.
You're comfortable owning cloud infrastructure. You can work with infrastructure-as-code such as Terraform and own the infrastructure your data systems depend on.
You communicate clearly across technical and non-technical teams. You can understand stakeholder problems in Finance, Network Integration, Product, and beyond, challenge assumptions when needed, and explain technical decisions and trade-offs.
You don't need to know the telecom industry.

Bonus Points If:

You have experience with GCP data services such as BigQuery, Pub/Sub, or Dataflow.
You know stream processing. We don't do much of it yet, but it's coming soon.
You've worked with dbt or similar transformation and modeling frameworks.
You're comfortable reading or contributing to application code in Go or Ruby when needed for an integration. Our backend is mostly written in those languages.
You've worked with financial, billing, metering, or usage data where errors have real downstream consequences.

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