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Senior Data Engineer AWS / Spark / Snowflake
Requirements
Senior Data Engineer AWS / Spark / Snowflake
Requirements
- Strong AWS experience; build, design & maintain data pipelines using Java Spark & PySpark
- Advanced SQL (complex queries, curation, views, performance tuning)
- Cloud data warehouses: Snowflake & AWS Redshift
- Performance optimization & troubleshooting of data jobs
- Agile, CI/CD, application resiliency & security best practices
- Data structures & serialization: JSON, Avro, Protobuf
- Big-data storage: Parquet, Iceberg
- Processing methods: batch, micro-batch, streaming
- Data modeling: Dimensional, Data Vault, Kimball, Inmon
- Knowledge of NoSQL databases and use cases
- Develop enterprise data models; design, build & maintain large-scale pipelines
- Drive data quality, governance, security & enterprise data protection controls
- Ensure data accessibility for analysts & data scientists
- Lead code reviews, mentor team, and make custom tool configurations
- Align data engineering practices with business goals and foster inclusive team culture