Data Engineer - Python

Data Engineer

What You'll Do

• Data Engineering & Pipeline Development
  Design and maintain backend data ingestion and embedding pipelines. Work hands-on with JupyterHub to set up environments, clone repositories, and run complex workflows.
• Graph Database & Knowledge Management
  Use Neo4j to build graph-based solutions that map knowledge articles and workflows. Contribute to schema design, data integration, and performance tuning.
• Data Quality & Optimization
  Troubleshoot data quality issues, optimize Spark jobs, and manage partition sizes. Convert ECS direct connections to IO Meet using Spark and Python.
• Authentication & Security
  Solve JWT authentication challenges, research Kerberos for secure cluster connectivity, and manage credentials for Oracle DB and API clients.
• DevOps & Collaboration
  Work with GitLab for source control and Jira for project tracking. Participate in migrations from Azure DevOps to modern tools.

Your Tech Playground

• Programming & Tools: Python, JupyterHub, GitLab
• Databases: Oracle DB, PostgreSQL + PGVector
• Big Data: Spark, Iceberg, S3, Parquet, CSV
• Graph & AI: Neo4j, LangChain, LLM integration
• Security: HashiCorp Vault, Kerberos
• Visualization: Power BI for dashboards and reporting

Skills That Make You Stand Out

• Strong experience in data engineering, profiling, and ETL processes
• Expertise in Spark job tuning and large-scale data exports
• Familiarity with embedding models like BGEM 3 and Nomic
• Ability to manage high-volume workloads and optimize compute resources
• Knowledge of cloud and on-prem integration (Azure + on-prem systems)