Data Science & Analytics
Virtasant
Virtasant is a cloud optimization and engineering consultancy that hires fully remote engineers across the Americas. It is looking for a Senior Serverless Spark Migration Engineer to lead the migration of enterprise Apache Spark workloads from on-premise Hadoop and Spark environments to cloud-native, serverless architectures on AWS and GCP. The listing is tagged USA, Canada, Latin America and Fully Remote, and the body states the hiring location as "Remote (Brazil, Mexico)" with coverage of "Pacific Hours (8:00 AM to 5:00 PM PST)". Candidates in Brazil or Mexico who can work a US Pacific schedule are the core audience. Salary is not stated in the listing and the employment arrangement is not spelled out (Virtasant's other Latin America roles have been full-time independent contractor engagements paid in USD, so ask during the process). Freshness evidence: Virtasant's own Teamtailor careers page shows a published time of 2026-09-25, with its other open roles dated differently, so this is a genuinely new posting.
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Assess and migrate production Spark workloads from on-prem Hadoop and Spark to cloud and serverless platforms. Design cloud architectures using EMR Serverless, AWS Glue, Lake Formation, Dataproc Serverless and BigQuery. Refactor legacy PySpark and Scala applications for cloud compatibility. Optimize performance and implement infrastructure as code. Build reusable migration tooling and automation frameworks.
8 or more years in data engineering, distributed systems or cloud engineering. 5 or more years of hands-on Apache Spark experience in enterprise settings. Proficiency in PySpark and/or Scala. Experience with both AWS and GCP. Knowledge of Hadoop ecosystems including HDFS, YARN and Hive. Based in Brazil or Mexico and able to work 8am to 5pm US Pacific time.
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This job title typically pays $120,230 to $199,130 a year (median $158,880) for similar roles in the US.
Estimate from US Bureau of Labor Statistics data, not provided by the employer.