Senior Backend Engineer - Data Core

JobgetherCreator data platform

Listing location: Germany, some overlap with GMT+3Full-TimeSenior

SalaryAnnual salary range of €80,000–€110,000, plus stock options.

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Job Details

Proven experience building large-scale backend or data systems where reliability, throughput, latency, scalability, and cost matter.
Ability to take systems from concept to production, including scoping, architecture, implementation, release, operation, measurement, and improvement.
Strong knowledge of distributed systems, including partial failures, retries, idempotency, backpressure, scaling, and fault tolerance.
Experience building and maintaining integrations with third-party APIs or other external dependencies.
Operational ownership experience using observability, monitoring, alerting, runbooks, and data-quality controls.
Experience with cloud infrastructure, particularly AWS.
Strong proficiency with TypeScript and Node.js.
Familiarity with databases, queues, object storage, infrastructure as code, and distributed cloud services.
Ability to work autonomously on ambiguous technical challenges and move projects forward without fully defined specifications.
Practical experience with proxy management, request routing, or high-volume traffic management is valuable.
Social-media APIs, large-scale data collection, data-quality frameworks, or freshness and coverage monitoring are bonus experience.

Build and evolve backend systems that collect and maintain 400M+ creator profiles across Instagram, TikTok, and YouTube.
Develop collection infrastructure to process billions of data points while maintaining freshness, coverage, and data quality.
Design resilient services that handle third-party API instability, rate limits, provider outages, platform changes, and partial failures.
Optimize requests, proxy usage, retries, storage, and compute to improve data-collection economics.
Design systems that determine which creators to collect and how frequently, balancing customer value with operational cost.
Own systems through requirements gathering, architecture, implementation, testing, deployment, monitoring, operation, and iteration.
Build observability, alerting, monitoring, and safeguards for collection failures, data-quality issues, coverage gaps, and freshness regressions.
Work with data, search, product, and engineering teams to establish reliable system interfaces and dependencies.
Evaluate technical approaches through production experiments before making larger investments.
Contribute to engineering standards, architecture decisions, code reviews, and technical direction.

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