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Gigs

Senior Data Engineer

Berlin
€90k – €125k/yr
Posted about 11 hours ago
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About Gigs

At Gigs, we're building the operating system for mobile services—a platform that lets tech companies embed global connectivity into their products effortlessly.

Just as Stripe lets any business add a payment button in seconds, Gigs empowers platforms to weave in connectivity—bridging the traditional world of telecom with modern tech. From fintechs launching mobile services to HR platforms offering work phone plans, we automate provisioning and remove telecom complexity.

Our team of around 150 people across the US and Europe, backed by nearly $100 million in funding from Ribbit Capital, Google, and Y Combinator. As one of the fastest-growing tech companies, bringing together early-stage engineers, product builders, and business athletes from companies like Stripe, Airbnb, and Shopify. We’re tackling deep technical and regulatory challenges to make connectivity truly seamless.

If you’re driven by curiosity, creativity, and the chance to shape the future of telecom, we’d love to hear from you.

Things We Care About

  • Speed: We move and we ship. We set bold deadlines and treat every week like it matters.
  • Ownership: If you see something broken, fix it. We don't wait for permission.
  • Customer Obsession: Our customers' product is our product.
  • Ambiguity: We're building frontier technology in a complex domain. You'll need sound judgment and good instincts to make decisions without complete information.
  • First principles: We don't ask how things have been done before. We ask why they were done that way at all.

The Role

As a Senior Data Engineer on the Data Team, you'll continue to build 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.

Reasons to use Rodeo

I’m in my final year doing Economics and I don’t know whether to apply for grad schemes now or do a masters first. What do you think?

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Graduate Consultant — 2026 Scheme

PwC·London, UK
£35,000/yr

Why you're a good match

Strong

Your economics background and your summer at a regional bank line up with what PwC looks for on the consulting scheme. Applications close in four weeks.

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Why you're a good match

You’ve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon — deadlines close within the month.

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Your summer at the bank plus your econometrics coursework map directly to the day-one responsibilities on this scheme — client modelling, market briefings, and deal support.

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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 modeling 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.

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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.

Work At Gigs

At Gigs, we value in-person collaboration. We believe the best ideas, decisions, and relationships are built when teams spend meaningful time together, and our culture is designed around that belief. We support flexibility where it makes sense. Some focused work can be done remotely, and not every role or week looks the same. You should expect regular time in one of our hubs, as well as occasional travel for team workshops, customer meetings, and Gigs Republic, our bi-annual company off-site. Our offices are designed to feel like home-inspired workspaces, with plants, thoughtful tools, and small, tight-knit teams that make collaboration feel natural, energizing, and effective.

What We Offer

At Gigs, we believe in rewarding excellence. We offer competitive compensation and stock options because we see you as a true partner in our growth. We also provide stipends for your home office or work setup, a budget for learning and development to fuel your career, and of course, a free phone and international data plan.

Want to learn more about our benefits, hubs, and what it’s like to work at Gigs? Check out our Careers page.

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Skills

Data engineering
Python
SQL
Data modeling
Dagster
Terraform
Cloud infrastructure
BigQuery
Snowflake
Databricks
Data pipelines
System architecture
Observability
Data quality
Stakeholder management

Location

Berlin, Germany

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