Senior Data Engineer | Snowflake | PySpark | AWS
Remote · MX
Job Summary
Senior Data Engineer to design, build, and evolve scalable cloud-native data pipelines and data warehousing solutions on Snowflake, PySpark, and AWS/Azure. You will develop end-to-end ETL/ELT workflows, process large-scale datasets with Spark/PySpark, design Snowflake data warehouse architectures, ensure performance, governance, and cost efficiency, write advanced SQL, and collaborate with data scientists, analysts, and software engineers. The role emphasizes production-grade pipelines, CI/CD with Git and Dockerized deployments, and improving reliability and observability of data platforms.
Required Qualifications
- 5+ years of professional experience in Data Engineering or related fields
- Strong experience designing and maintaining scalable data pipelines
- Deep understanding of ETL / ELT best practices
- Strong experience with large-scale data processing architectures
- Proven experience with batch data processing
- Strong experience with data warehousing concepts
- Advanced Python
- Strong hands-on experience with Apache Spark / PySpark
- Advanced SQL (complex queries, optimization, transformations)
- Strong experience processing large structured and unstructured datasets
- Hands-on experience with AWS or Azure
- Experience building cloud-native data solutions
- Experience with Docker
- Experience with CI/CD pipelines
- Strong knowledge of Git / version control
- Strong hands-on experience with Apache Airflow
- Experience designing workflow orchestration pipelines
- Scheduling, monitoring, and failure recovery strategies
- Strong expertise in Snowflake (MUST HAVE)
- Snowflake data warehouse design
- Snowflake development
- Query and warehouse optimization
- Performance tuning and cost efficiency
- Cloud data warehouse architecture best practices
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