Data Engineer

This is a fully remote position, open to applicants in Germany.

📋 Description

• Oversee, enhance, and drive the advancement of the data lake architecture

• Develop data pipelines to ingest detailed, near real-time machine telemetry and publish it to the data lake

• Generate and modify queries based on machine data to deliver insights on performance and various metrics

• Ensure the integrity of clean data sets with quality controls for utilization by business teams

• Manage and administer cloud platforms and accounts that host data and data-intensive applications

• Collaborate with software engineers to guarantee proper system instrumentation for capturing all data outflows

• Establish alerts and mechanisms to proactively detect data issues or deviations in metrics

⛳️ Requirements

• Minimum of 3 years of experience in Python data engineering

• Experience with production ETL/ELT pipelines and data services using Python

• Strong engineering practices including Git, code review, testing, and linting

• Proficient in PostgreSQL and analytical SQL

• Strong expertise in data modeling for analytics

• Practical experience with AWS services such as S3, Lambda, Glue, Athena/Presto

• Familiarity with Azure, including Blob Storage

• Management of secure credentials and IAM across different environments

• Experience with event-driven architectures and message-queue pipelines

• Knowledge of incremental sync patterns

• Ability to create REST API connectors to SaaS platforms like HubSpot and ClickUp

• Experience in MongoDB document-data modeling and querying

• Operating MongoDB Atlas across multiple environments

• Competence in safe data migrations

• Experience in building and maintaining Airtable solutions

• Skills in migrating Airtable solutions to more robust databases as data volume increases

• Conduct data validation and consistency checks across systems

• Ability to perform production data backfills and cleanup

• Experience in building BI dashboards; preference for Metabase, with Streamlit, Superset, Power BI, or Tableau also acceptable

• Familiarity with Docker and Linux for containerized services

• Experience in GitHub Enterprise administration and access governance

• Proficient with AI developer tools such as Claude and GitHub Copilot

• Knowledge of metrics and alerting using Prometheus, Grafana, and node exporter

• Experience with CloudWatch alarms for cloud workloads

🏝️ Benefits

• High level of collaboration and autonomy

• A transparent culture where each individual is highly valued

• Opportunities for professional skill and knowledge development through ownership of challenging tasks and responsibilities, with support from leads and peers

• A “getting things done” mindset

• Access to cutting-edge technologies

• Complimentary Health Insurance