Senior Data Engineer, Platform Data

Job not on LinkedIn

🕒 May 26

🇩🇪 Germany – Remote

💵 €65k - €70k / year

⏰ Full Time

🟠 Senior

🚰 Data Engineer

👻 Ghost score 45%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Leadfeeder

WebsiteLinkedInAll Job Openings

51 - 200 employees

💼 Consulting

📣 Marketing

🛍️ eCommerce

💰 Series A on 2019-04

Consulting • Marketing • eCommerce

Leadfeeder is a website visitor analytics software that helps identify which companies visit a website, providing insights into their behavior and engagement. By integrating with popular tools like Google Analytics, MailChimp, and Salesforce, Leadfeeder serves as a comprehensive solution for lead generation, account-based marketing, and sales intelligence. The software aims to enhance B2B sales efforts by revealing potential leads in real-time, making it easier for sales teams to connect with decision-makers.

📋 Description

• Design, build, and operate production data pipelines powering Leadfeeder’s product features, from ingestion through enrichment, processing, and serving. • Build and maintain streaming and real-time ingestion systems for scalable, low-latency event data movement. • Own cloud infrastructure for compute, storage, networking, security, and observability, managed as code. • Collaborate with product and ML engineers to deliver datasets and pipelines for product-facing features and AI/ML workflows. • Implement data quality, observability, and reliability controls across pipelines. • Drive engineering practices including code review, testing, CI/CD for data, infrastructure-as-code, performance tuning, and cost discipline. • Partner with engineering, product, and ML teams to translate product requirements into scalable, well-documented data systems.

🎯 Requirements

• 10+ years of hands-on experience in data and/or software engineering, with a leading role in production data pipelines that power product or customer-facing systems. • Production-grade Python, strong SQL, code review, testing, CI/CD, and operational ownership. • Deep cloud infrastructure experience with AWS or equivalent, including compute, storage, streaming, identity and access management, networking, and infrastructure-as-code. • Experience with streaming or real-time data ingestion using Kafka, Kinesis, Flink, Spark Streaming, or similar. • Experience with modern data warehouse/lakehouse technologies such as Snowflake, BigQuery, Redshift, Databricks, or Athena. • Hands-on experience with data transformation tooling, particularly dbt. • Track record of building and operating distributed data systems at scale, with attention to performance, reliability, and cost. • Familiarity with data quality and observability tooling and practices. • Background in enabling AI/ML workloads on production data. • Strong written and verbal communication skills in English. • Ability to collaborate with engineering, product, and non-engineering stakeholders. • Comfortable working in a fully remote environment. • Be physically located within Europe. • Nice to have: knowledge of data cataloguing tools, data contracts frameworks, or data mesh principles. • Nice to have: background in B2B SaaS and familiarity with intent data, web event data, CRM, product analytics, billing, and support tooling.

🏖️ Benefits

• The chance to work with a very knowledgeable, high-achieving and fun team. • An international, diverse, dynamic and committed work environment. • The opportunity to work remotely, with a flexible work schedule. • Mental health support with Auntie. • Transparent compensation practices: candidates invited to any interview stage receive the salary range and key compensation details before their first conversation.