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Sr. AWS Data Engineer - Airflow & ETL ( AWS, Pyspark, Databricks)
3-20 years
Remote
1 vacancy
Sr. AWS Data Engineer - Airflow & ETL ( AWS, Pyspark, Databricks)
Artmac Soft
posted 3mon ago
Job Role Insights
Flexible timing
Key skills for the job
Job Description
- Experience in data engineering with a strong focus on ETL processes and data pipeline development.
- Proficiency in using Airflow for orchestrating complex data workflows.
- Extensive experience with AWS services (eg, S3, Lambda, Glue, Redshift).
- Strong programming skills in PySpark, with a deep understanding of distributed data processing.
- Hands-on experience with Databricks for data processing and analytics.
- Experience with additional big data technologies such as Kafka, Hadoop, or Snowflake.
- Familiarity with data visualization tools like Tableau, Power BI, or similar.
- Experience with CI/CD tools and practices for data pipelines.
- Certifications in AWS or Databricks are a plus.
- Familiarity with SQL and relational databases for data extraction and manipulation.
- Proven experience with data modeling, data warehousing, and building scalable data solutions.
- Knowledge of best practices in data management, including data governance and data security.
- Strong problem-solving skills and ability to troubleshoot complex data issues.
- Excellent communication and collaboration skills, with the ability to work effectively in a team environment.
- Optimize data pipelines for performance, scalability, and reliability.
- Implement best practices for data governance, data quality, and data security.
- Monitor and troubleshoot ETL processes to ensure data accuracy and integrity.
- Work in an agile environment, actively participating in sprint planning, daily stand-ups, and retrospectives.
- Document data workflows, processes, and technical specifications to ensure clear communication and knowledge sharing within the team.
- bachelors degree in Computer Science, Information Technology, or a related field.
Employment Type: Full Time, Permanent
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