
Senior Data Pipeline Architect
2 weeks ago
We are seeking a highly skilled Data Engineer to join our team. As a key member of our data engineering team, you will be responsible for designing, developing, and maintaining complex data pipelines using Python.
Responsibilities- Design and Develop Complex Data Pipelines:
- Collaborate with cross-functional teams to understand data requirements and architect robust solutions within the AWS environment.
- Implement data integration and transformation processes to ensure optimal performance and reliability of data pipelines.
- Optimize and fine-tune existing data pipelines / Airflow to improve efficiency, scalability, and maintainability.
- Work Closely with AWS Services:
- Develop and maintain documentation for data pipelines, processes, and system architecture.
- Stay updated with the latest industry trends and best practices related to data engineering and AWS services.
- Requirements and Qualifications:
- Bachelor's degree in Computer Science, Engineering, or a related field.
- Proficiency in Python, PySpark, and SQL for data processing and manipulation.
- Min 5 years of experience in data engineering, specifically working with Apache Airflow and AWS technologies.
- Strong knowledge of AWS services, particularly S3, Glue, EMR, Redshift, and AWS Lambda.
- Understanding of Snowflake Data Lake is preferred.
- Preferred Qualifications:
- AWS certification(s) related to data engineering or big data.
- Experience working with big data technologies like Snowflake, Spark, Hadoop, or related frameworks.
- Familiarity with other data orchestration tools in addition to Apache Airflow.
- Knowledge of version control systems like Bitbucket, Git.
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