Lead Data Engineer – Python
4 days ago
Experience Level: 10 to 12 years of relevant IT experience Key Responsibilities:
- Design, develop, test, and maintain scalable ETL data pipelines using Python.
- Architect the enterprise solutions with various technologies like Kafka, multi-cloud services, auto-scaling using GKE, Load balancers, APIGEE proxy API management, DBT, using LLMs as needed in the solution, redaction of sensitive information, DLP (Data Loss Prevention) etc.
- 10 to 12 years of hands-on experience in Python for backend or data engineering projects.
- Strong understanding and working experience with GCP cloud services (especially Dataflow, BigQuery, Cloud Functions, Cloud Composer, etc.).
- Solid understanding of data pipeline architecture, data integration, and transformation techniques.
- Experience in working with version control systems like GitHub and knowledge of CI/CD practices.
- Experience in Apache Spark, Kafka, Redis, Fast APIs, Airflow, GCP Composer DAGs.
- Strong experience in SQL with at least one enterprise database (SQL Server, Oracle, PostgreSQL, etc.).
- Experience in data migrations from on-premise data sources to Cloud platforms.
- Experience working with the Snowflake cloud data platform.
- Hands-on knowledge of Databricks for big data processing and analytics.
- Familiarity with Azure Data Factory (ADF) and other Azure data engineering tools.
- Excellent problem-solving and analytical skills.
- Strong communication skills and ability to collaborate in a team environment.
- Bachelor's degree in Computer Science, a related field, or equivalent experience.
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