Data Engineer

Key Responsibilities:

Data Engineering & Pipelines

• Develop and maintain robust data pipelines for large and complex datasets.
• Extract, transform, and load (ETL) data from various sources and file formats.
• Handle time series data and optimize pipelines for performance.
• Monitor, troubleshoot, and ensure optimal operation of data systems.
• Perform root cause analysis for any production issues.

Technology & Tools

• Hands-on coding in Python; familiarity with .NET or Kafka is a plus.
• Experience with Docker and Kubernetes for containerization and orchestration.
• CI/CD pipelines and Git for version control.
• Data modeling, workflow management, and large-scale dataset handling.
• Optional: Dashboard development using Grafana or similar reporting tools.

Collaboration & Communication

• Work closely with development teams and product owners to deliver high-quality solutions.
• Communicate effectively across teams and contribute to collaborative problem-solving.
• Participate in agile development processes and code reviews.