
Big Data Engineer
1 day ago
We are looking for a skilled Big Data Engineer to design, develop, and maintain large-scale data pipelines using PySpark and Databricks.
Key Responsibilities:
- Design and implement scalable data architectures using PySpark and Databricks.
- Develop and optimize Spark applications using Spark UI and performance tuning techniques.
- Work with large datasets and implement best practices for partitioning, caching, join optimization, and cluster resource management.
- Build efficient data ingestion, transformation, and aggregation logic from multiple sources using Kafka and other streaming technologies.
- Leverage AWS services such as S3, EMR, Lambda, Glue, Redshift, etc., for cloud-based data processing and orchestration.
- Implement workflows using tools such as Airflow or Databricks Workflows.
- Utilize skills in distributed data processing, data formats like Parquet, Avro, and OyC, and exposure to orchestration tools (Airflow, Databricks Workflows).
Requirements:
- 5+ years of experience in designing and developing big data solutions using PySpark and Databricks.
- Strong knowledge of data engineering principles, including data pipelining, data warehousing, and ETL processes.
- Experience with cloud-based data platforms, including AWS services.
- Excellent problem-solving skills and ability to troubleshoot complex data processing issues.
- Strong communication and collaboration skills.
Benefits:
- Competitive salary and benefits package.
- Ongoing training and professional development opportunities.
- Collaborative and dynamic work environment.
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