
Only 24h Left: Data Engineer
3 weeks ago
Must-Have Skills :
- Strong Experience in PySpark
- Hands-on expertise in building scalable data pipelines using PySpark.
- Proficiency in using Spark SQL, DataFrame, and RDD APIs to implement complex business logic.
- Proficient Programming Skills
- Solid coding skills in Python (preferred), with strong fundamentals in data structures, algorithms, and software engineering principles.
- Data Pipeline Development
- Proven experience designing, developing, and maintaining batch and streaming data pipelines.
- Understanding of ETL/ELT processes and best practices for data transformation, data quality, and performance optimization.
- Knowledge of Modern Data Engineering Ecosystem
- Familiarity with the current data engineering landscape including distributed data processing, storage systems, and workflow orchestration tools.
- Tools/technologies could include Apache Airflow, dbt, Delta Lake, etc.
- Cloud Data Platform Experience (Preferably AWS)
- Experience working with cloud services such as:
- AWS S3 (data lake)
- AWS Glue / EMR (for Spark workloads)
- AWS Lambda, Step Functions, or similar for orchestration/integration
- Redshift or other cloud data warehouses
- Spark API Expertise for Business Logic Implementation
- Ability to choose and apply the right Spark APIs (DataFrame, Dataset, RDD) for performance-efficient implementation of business logic at scale.
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