Sr. Data Engineer I (Python/AWS)

TL;DR

Sr. Data Engineer I (Python/AWS): Designing and operating robust data lakehouse solutions utilizing open table formats like Apache Iceberg with an accent on scalable data pipelines and cloud infrastructure. Focus on optimizing query performance for analytical workloads and implementing Infrastructure as Code for reliable platform deployments.

Location: Remote in Argentina or Mexico

Salary: $62,000 - $74,000 a year

Company

hirify.global is a mission-driven financial software company that uses machine learning to create better digital-first experiences for distressed borrowers.

What you will do

• Design, build, and operate scalable data lakehouse solutions using Apache Iceberg.
• Construct robust data pipelines and implement transformation logic for batch and streaming data.
• Develop data models and curated data products to power reporting and machine learning applications.
• Manage AWS cloud infrastructure using Infrastructure as Code (Terraform) and Kubernetes.
• Monitor workloads to ensure high data quality, freshness, and adherence to SLAs.
• Collaborate with Data Services and Data Science teams to evolve the data platform.

Requirements

• Bachelor's degree in Computer Science, Engineering, or a related technical field.
• 4+ years of engineering experience, including 2+ years in data-focused roles.
• Proven experience implementing data lake and data warehousing platforms.
• Strong proficiency in Python and SQL for data engineering.
• Hands-on experience with the AWS ecosystem (S3, Glue Catalog, IAM, Secrets Manager).
• Must be based in Argentina or Mexico.

Nice to have

• Experience with Airflow, DBT, and Snowflake.
• Experience with streaming processing technologies like Flink or Spark Streaming.
• Familiarity with Domain-Driven Design and event-driven architectures.
• Relevant technical certifications.

Culture & Benefits

• Unlimited PTO.
• Medical benefit contributions in accordance with local laws.
• Opportunity to do impactful work within a diverse and inclusive team.