About the Role

We are seeking an experienced Data Engineer with strong Python expertise to design, build, and optimize scalable data pipelines and ETL/ELT processes. You’ll collaborate with cross-functional teams to ensure data reliability, automate deployments, and drive performance improvements in our data infrastructure.

Key Responsibilities

✔ Data Pipeline Development:

• Design, develop, and maintain ETL/ELT pipelines with a focus on scalability and maintainability.
• Implement unit/integration testing to ensure data quality and system robustness.

✔ Collaboration & Optimization:

• Partner with data teams to translate requirements into technical solutions.
• Troubleshoot and optimize data storage, processing, and performance.
• Automate deployments and monitoring for CI/CD workflows.

✔ Best Practices:

• Adopt DevOps practices and Agile methodologies in development cycles.
• Document architecture and processes for knowledge sharing.

Mandatory Qualifications

✅ Education: Bachelor’s degree in Computer Science, IT, or related field.

✅ Experience:

• 5+ years in software/data engineering with Python proficiency.
• Strong background in unit/integration testing.
• Familiarity with DevOps and Agile.

✅ Skills:

• Excellent problem-solving and analytical abilities.
• Strong team player with effective communication.

Preferred Skills (Nice-to-Have)

🔹 Cloud platforms: AWS, Kubernetes (K8s).

🔹 Data tools: Snowflake, Apache Spark/Hive, Airflow/Dagster/Prefect.

🔹 Monitoring: Datadog, GitHub workflows.