Lead Data Platform Engineer

Remote from: Europe
Annual salary: Undisclosed
Salary information is not provided for this position. Check our Salary Directory to estimate the average compensation for similar roles.
Department: Software Engineering
Employment type: Full Time,
Job posted: 12 Jun 2026
Apply before: 12 Jul 2026
Experience level: Senior
Views / Applies: 15 / 3

A great new home for your SaaS business

Computer Software
2018

AI Summary

This is a hands-on Lead Data Platform Engineer role at INFOnline, part of saas.group, responsible for owning and evolving a GCP-native data platform that processes billions of events for audience measurement. You will take full ownership of the platform post-migration, focusing on stability, scalability, data quality, and cost efficiency. The role involves setting technical direction, mentoring, and driving AI-native engineering practices. Immediate impact includes auditing the architecture, improving monitoring and observability, and establishing engineering standards. This is a technical leadership position requiring deep GCP and Golang expertise.

Role DNA

Job Complexity

Easy Hard

Pace & Pressure

Relaxed Fast-paced

Autonomy Level

Guided Full Ownership

Communication Load

Independent Highly Collaborative

AI Insight The role requires deep technical expertise in GCP, Golang, and data platforms, plus the ability to set strategy and mentor others, making it highly challenging (4 out of 5).

Salary Analysis

AI Insight No salary was provided in the listing. Based on market data for a Lead Data Platform Engineer in the US, the typical range is $130,000-$200,000, with a median around $160,000. This role likely offers competitive compensation given the seniority and technical requirements.

Key Skills

Data Engineering GCP Golang BigQuery Dataflow Cloud Run Pub/Sub SQL Data Pipelines Platform Engineering

Cover Letter Sample

I am writing to express my interest in the Lead Data Platform Engineer position at INFOnline. With over 5 years of hands-on experience in data platform engineering and a strong background in Go and GCP services like BigQuery, Pub/Sub, and Dataflow, I am confident I can drive the evolution of your cloud-native platform.

In my previous role, I led the migration of critical data infrastructure to GCP, establishing robust monitoring, data quality controls, and cost optimization practices. I take pride in being both a strategic thinker and a coder who can set technical direction while staying close to the code.

I am particularly excited about the emphasis on AI-native engineering practices, as I have already integrated AI-assisted development into my workflow to improve code quality and accelerate delivery.

I look forward to the opportunity to contribute to INFOnline's platform and help shape its future.

Possible Interview Questions

Can you describe your experience with GCP services like BigQuery, Pub/Sub, and Dataflow, and how you have used them in production data pipelines?

I have extensive experience building and maintaining data pipelines on GCP. For example, I used Pub/Sub for real-time event ingestion, Dataflow for stream processing, and BigQuery for analytics. I also optimized costs by partitioning tables and using clustering keys.

How do you approach monitoring and observability for large-scale data platforms?

I implement monitoring using Stackdriver and custom metrics, set up alerts for data latency and quality issues, and use dashboards for real-time visibility. I also ensure proper logging and tracing to quickly debug failures.

Describe a time you had to make a trade-off between stability and new features. How did you decide?

In a previous role, we needed to upgrade a critical component but risked downtime. I proposed a canary deployment with rollback plan, prioritized stability by extensive testing and monitoring, and phased the rollout to minimize impact.

How do you mentor less experienced engineers while still staying hands-on?

I pair program on complex tasks, conduct code reviews focusing on design patterns, and set up weekly knowledge-sharing sessions. I also delegate ownership of modules while providing guidance and clear acceptance criteria.

This role emphasizes AI-native engineering. How have you integrated AI into your development workflow?

I use AI coding assistants for boilerplate generation, test case creation, and refactoring. For example, I prompted an AI tool to generate BigQuery SQL queries from natural language description, which I then reviewed and optimized.

This role is part of our INFOnline team, one of our exciting brands at saas.group.

INFOnline powers digital audience measurement for the German and Austrian media industry. Our systems process billions of events and deliver the trusted reach and engagement metrics used by publishers, advertisers, agencies, IVW and OEWA.

As part of saas.group, we have been modernizing our business-critical infrastructure and moving towards a fully cloud-native architecture on GCP. The major migration work is complete. Now we are looking for a strong technical owner to run, harden, scale and evolve the new platform.

Profile Overview

We’re looking for a technically deep, hands-on Lead Data Platform Engineer to take full ownership of INFOnline’s central data platform from raw event ingress through processing, aggregation, data modeling and reporting delivery.

You will take ownership of a newly built GCP-native data platform as it moves from completed migration into long-term production operation, optimization and continuous evolution.

This is not a role where you simply follow someone else’s roadmap. You will help define how the platform should mature: where we need stronger observability, better data quality controls, clearer ownership boundaries, improved documentation, cost efficiency and more scalable operating models.

This is a hands-on technical leadership role. You will set technical direction, make architecture decisions, establish engineering standards, mentor others and still work close to the code and systems.

On top of that, you will help drive AI-native engineering practices using coding agents, AI-assisted testing, documentation, refactoring and incident analysis to increase engineering speed and quality.

Your immediate impact in the first 3-6 months will be:

Audit and map the existing cloud and data platform architecture identify critical risks, dependencies, and improvement opportunities
Take ownership of core platform components from data ingress to reporting, supported by structured knowledge transfer where needed
Establish full internal ownership of the new cloud-native data platform
Improve data quality controls, validation processes and operational safeguards
Build a pragmatic post-migration roadmap focused on stability, scalability, data quality, cost efficiency and business continuity
Strengthen monitoring, alerting, and observability for business-critical data workflows and IVW/OEWA delivery pipelines
Establish engineering standards around documentation, code reviews, testing and AI-native development practices

Your responsibilities

Own the end-to-end data platform roadmap and drive its execution from architecture decisions to day-to-day platform operations
Take accountability for data ingress, streaming processing, batch aggregation, data modeling, quality, delivery and reporting logic
Ensure reliability, scalability and performance through strong monitoring, observability and incident management practices
Continuously improve the new GCP-native platform with a focus on stability, cost efficiency, maintainability and business continuity
Collaborate closely with Product, Customer Success and Leadership to translate business requirements into scalable technical solutions
Drive AI-native engineering adoption, including AI-assisted coding, refactoring, testing, documentation and code reviews and establish standards for safe, effective use
Work with external specialists where useful and establish sustainable internal ownership of all critical platform components

What You bring to the table

5+ years of experience in Data Engineering, Data Platform Engineering, or Platform Engineering in production environments
Solid Go (Golang) proficiency is required. Our core backend systems, including ingress collectors, Pub/Sub processors, Dataflow jobs, batch loaders, controllers and CLI tools are written in Go.
Strong hands-on experience with GCP Cloud Run, Pub/Sub, BigQuery, Dataflow, Cloud Storage, Cloud SQL
Strong SQL and analytical data modeling skills; familiarity with SQLMesh (or similar dbt-style orchestration tools) is a significant plus
Practical experience with Terraform / IaC, CI/CD pipelines, and containerized workloads (Docker; Cloud Run-style serverless, not cluster Kubernetes)
Experience with Protobuf or comparable schema definition and serialization frameworks
Familiarity with IVW, OEWA or comparable digital audience measurement standards or a genuine interest in the web analytics domain and the ability to ramp quickly
Experience with AI coding assistants and coding agents (Claude Code, Codex, or similar) and sound judgment in reviewing AI-generated code for quality, security, and operational risk
Excellent communication skills with both technical and non-technical stakeholders
Fluent German (C1) required; good English for technical documentation and saas.group collaboration

What’s in it for You

Ultimate flexibility: We’re 100% remote. You can work from wherever you like, whenever you like.
Freedom and autonomy: We’re a high-trust team, and you’ll be given lots of flexibility to solve problems in your own way, with plenty of help from the team when you need it.
Minimum bureaucracy: We don’t like to get bogged down with meetings and red tape. We like to be efficient and keep momentum steady & sustainable.
Small & friendly team: We help each other out, have fun, and joke around.
Our network: We are a community of entrepreneurial SaaS professionals that regularly exchange ideas, knowledge, learning and expertise with each other internally.

INFOnline is part of saas.group and we have a shared goal of succeeding together.

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saas.group is committed to creating a diverse and inclusive workplace. We are proud to be an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status. We celebrate diversity and are committed to creating an inclusive environment for all employees. If you’re passionate about working with a team that values innovation, excellence, and fairness, we encourage you to apply.

We believe in fair and transparent pay. Salary ranges at saas.group are location-adjusted, targeting local market medians for a remote-first environment, and will be shared with our potential future employees in writing before your first interview – so you have everything you need to evaluate the opportunity.

Apply now >