Senior Data Platform Engineer (AWS)

TL;DR

Senior Data Platform Engineer (AWS): Building and optimizing data pipelines and lakehouse architecture for a scientific data cloud platform with an accent on parsing proprietary lab instrument formats and harmonizing complex scientific data. Focus on designing scalable data models, implementing Databricks Lakehouse solutions on AWS, and ensuring high-quality production delivery for biopharma clients.

Location: Must be based in Argentina, Brazil, or Colombia

Company

hirify.global is an AI-native consulting and technology services firm delivering enterprise transformation across cloud, data, software engineering, and artificial intelligence.

What you will do

• Own, prototype, implement, and deploy Databricks Lakehouse pipelines on AWS.
• Research and prototype data acquisition strategies for scientific lab instrumentation.
• Build file parsers for diverse instrument output formats including binary, text, and spreadsheet files.
• Design and build robust data models, Python pipelines, and comprehensive test suites.
• Collaborate directly with customers to validate solutions against scientific requirements.
• Facilitate project post-mortems to drive continuous improvement across engagements.

Requirements

• 5+ years of professional experience in Python and SQL.
• Hands-on experience with Databricks Lakehouse architecture on AWS.
• Strong working knowledge of AWS Redshift.
• Proficiency with ETL/ELT pipeline development using Airflow.
• Must be based in Argentina, Brazil, or Colombia.
• Experience across the AWS data stack including ECS, S3, Athena, and RDS.

Nice to have

• Experience with Elasticsearch.
• Background in scientific instrumentation, lab workflows, or biopharma data.
• Graduate degree in Chemistry, Biology, Computer Science, or related fields.
• Experience parsing proprietary binary file formats.

Culture & Benefits

• Work on real-world AI-driven projects across diverse industries.
• Collaborate within a global, inclusive team environment.
• Access to continuous learning and professional development opportunities.
• Focus on innovation and ethical AI standards.