Backend Engineer – Data & Orchestration

Melotech

. Own and operate the company’s data platform, keeping it reliable, clean and increasingly simple .

Posted 9/15/2026full-timeRemote • GermanyMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in managing and operating data platforms, ensuring data reliability and integrity through advanced Python programming, event-driven pipeline design, and effective monitoring. Capable of guiding junior engineers while communicating technical concepts to non-technical stakeholders.

Highest-signal resume keywords

Advanced Python ProgrammingEvent-Driven Pipeline DesignCI/CD and Infrastructure as CodeDatabase Management (Postgres, MongoDB, Redshift)Monitoring Tools (Datadog)

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

PythonJavaScriptTypeScriptEvent-Driven PipelinesScraper ManagementDatabase ChecksData Reliability ChecksAccess Control ManagementAI Tool UtilizationFault-Tolerant Systems

Soft Skills

Team LeadershipTechnical CommunicationDocumentation SkillsProblem-SolvingAdaptability

Tools & Technologies

AirflowDagsterDockerTerraformCloud Infrastructure

Industry Keywords

Data Platform ManagementProduction SystemsMonitoring and AlertingData IntegrationAccess Reviews

Tech Stack

Tools & technologies

AirflowAmazon RedshiftCloudDockerJavaScriptMongoDBPostgresPythonTerraformTypeScript

About the role

Key responsibilities & impact

Own and operate the company’s data platform, keeping it reliable, clean and increasingly simple
Maintain scrapers and platform integrations across unreliable sources, rate limits, anti-bot measures and changing APIs
Own event-driven pipelines end to end, from orchestration through databases and warehouses
Build monitoring and alerting for services and integrations
Implement freshness, volume, schema and value checks for data reliability
Work on production backend services and APIs, including JavaScript backends
Own CI/CD, infrastructure as code and cloud infrastructure for data systems
Manage access controls and secrets, including access for AI tools
Consolidate and document the data system and remove obsolete components
Explain data capabilities and limitations to non-technical colleagues
Guide junior engineers as the team grows

Requirements

What you’ll need

3 to 10 years of hands-on engineering experience
Experience operating real production systems in small or fast-growing companies
Advanced Python, including async code and long-running data jobs
Backend experience with production services and APIs, including basic JavaScript or TypeScript backends
Experience operating unreliable external sources in production, including scrapers, platform APIs or unofficial endpoints
Knowledge of proxies, rate limits and anti-bot measures
Experience designing and running event-driven, fault-tolerant pipelines handling millions of records per day
Experience with Airflow, Dagster or task queues
Experience with databases such as Postgres, ClickHouse, MongoDB or Redshift
Knowledge of database and infrastructure operating costs
Experience implementing freshness, volume, schema and value checks
Experience with Datadog or an equivalent monitoring tool
Comfort with Docker, Terraform, CI/CD and cloud
Ideally, experience with access reviews, role-based access and secrets management
End-to-end ownership of a messy data setup at a smaller company
Ability to document and maintain systems
Ability to explain trade-offs to non-technical colleagues
Experience guiding junior engineers or leading a small team
Strong engineering fundamentals and sound technical judgment
Ability to use AI coding tools to accelerate development without replacing engineering judgment
Ability to thrive in a fast-paced and performance-oriented environment

Benefits

Comp & perks

Equity in the business
Remote work with complete freedom over your life
Global offsites and regular meetings around the world
Competitive salary (amount not specified)