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PythonWe are looking for a skilled and passionate Data Engineers with a strong foundation in Python programming and hands-on experience working with APIs, AWS cloud, and modern development practices. The ideal candidate will have a keen interest in building scalable backend systems and working with big data tools like PySpark.
Key Responsibilities:
- Write clean, scalable, and efficient Python code.
- Work with Python frameworks such as PySpark for data processing.
- Design, develop, update, and maintain APIs (RESTful).
- Deploy and manage code using GitHub CI/CD pipelines.
- Collaborate with cross-functional teams to define, design, and ship new features.
- Work on AWS cloud services for application deployment and infrastructure.
- Basic database design and interaction with MySQL or DynamoDB.
- Debugging and troubleshooting application issues and performance bottlenecks.
Required Skills & Qualifications:
- 4+ years of hands-on experience with Python development.
- Proficient in Python basics with a strong problem-solving approach.
- Experience with AWS Cloud services (EC2, Lambda, S3, etc.).
- Good understanding of API development and integration.
- Knowledge of GitHub and CI/CD workflows.
- Experience in working with PySpark or similar big data frameworks.
- Basic knowledge of MySQL or DynamoDB.
- Excellent communication skills and a team-oriented mindset.
Nice to Have:
- Experience in containerization (Docker/Kubernetes).
- Familiarity with Agile/Scrum methodologies.
Python
We are looking for a Senior Data Engineer with strong expertise in GCP, Databricks, and Airflow to design and implement a GCP Cloud Native Data Processing Framework. The ideal candidate will work on building scalable data pipelines and help migrate existing workloads to a modern framework.
- Shift: 2 PM 11 PM
- Work Mode: Hybrid (3 days a week) across Xebia locations
- Notice Period: Immediate joiners or those with a notice period of up to 30 days
Key Responsibilities:
- Design and implement a GCP Native Data Processing Framework leveraging Spark and GCP Cloud Services.
- Develop and maintain data pipelines using Databricks and Airflow for transforming Raw → Silver → Gold data layers.
- Ensure data integrity, consistency, and availability across all systems.
- Collaborate with data engineers, analysts, and stakeholders to optimize performance.
- Document standards and best practices for data engineering workflows.
Required Experience:
- 7-8 years of experience in data engineering, architecture, and pipeline development.
- Strong knowledge of GCP, Databricks, PySpark, and BigQuery.
- Experience with Orchestration tools like Airflow, Dagster, or GCP equivalents.
- Understanding of Data Lake table formats (Delta, Iceberg, etc.).
- Proficiency in Python for scripting and automation.
- Strong problem-solving skills and collaborative mindset.
⚠️ Please apply only if you have not applied recently or are not currently in the interview process for any open roles at Xebia.
Looking forward to your response!
Best regards,
Vijay S
Assistant Manager - TAG
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