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Description supplied by the original job listing.
Senior Data Engineer – Python/Spark Architect
We’re looking for a Senior Data Engineer with strong hands-on experience in Python, Spark, Databricks, and AWS who can design and optimize large-scale data systems.
Key requirements:
6+ years of experience in Data Engineering or distributed systems.
Strong Python and advanced SQL skills.
Mandatory: hands-on experience with Apache Spark and Databricks.
Experience building and optimizing large-scale ETL/ELT pipelines.
Strong AWS experience, especially S3, Glue, EMR, and Kinesis.
Experience with Airflow for orchestration.
Knowledge of data modeling, such as Kimball.
Experience with Snowflake or Redshift.
Strong understanding of performance, scalability, data quality, and monitoring.
Fluent English.
Based in Brazil, Mexico and Colombia / fully remote.
Nice to have:
Terraform / Infrastructure as Code.
Kafka or Kinesis.
Geospatial data experience.
Ideal profile:
A Senior Data Engineer / Spark Architect who has actually designed, built, and optimized high-volume Spark/Databricks pipelines on AWS, rather than someone who has only basic exposure to these technologies.
Work arrangement
Yes
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