TL;DR

Software Engineering SMTS (Data Science/ML): Building scalable data processing and analytics services utilizing big data stack, including Spark, Trino, Airflow, and Kafka, to support real-time and batch data workflows with an accent on system resilience, availability, and performance. Focus on resolving complex technical challenges and driving innovations.

Location: San Francisco, Los Angeles or Seattle.

Company

%hirify_global% is a technology-driven team focused on enabling scalable, high-performance data processing and analytics.

What you will do

Develop scalable data processing and analytics services utilizing big data stack, including Spark, Trino, Airflow, and Kafka, to support real-time and batch data workflows.
Design, develop, and operate resilient distributed systems that manage thousands of compute nodes across multiple data centers, ensuring scalability and high availability.
Resolve complex technical challenges and drive innovations that enhance system resilience, availability, and performance.
Manage the full lifecycle of services, balancing live-site reliability, feature development, and technical debt retirement.
Participate in the team’s on-call rotation to address complex, real-time issues, keeping critical services operational and highly available.
Provide mentorship and technical guidance to junior engineers, fostering growth, collaboration, and knowledge-sharing within the team.

Requirements

Bachelor’s or Master’s in Computer Science, Engineering, or a related field with 5+ years of experience in distributed systems, big data, or similar roles.
Proficiency in cloud platforms (AWS, GCP, or Azure), containerization (Docker, Kubernetes), and infrastructure-as-code (Terraform, Ansible).
Hands-on experience with Hadoop, Spark, Trino (or similar SQL query engines), Airflow, Kafka, and related ecosystems.
Strong skills in Python, Java, Scala, or other programming languages relevant to distributed systems.
Solid knowledge of distributed computing principles, data partitioning, fault tolerance, and performance tuning.
Proven ability to troubleshoot complex system issues, optimizing for speed, efficiency, and scale.

Culture & Benefits

Focus on enabling scalable, high-performance data processing and analytics.
Use cutting-edge tools like Spark, Trino, Airflow, and Kafka to build resilient, scalable infrastructure.
Opportunity to mentor and guide team members, fostering growth, collaboration, and knowledge-sharing within the team.

Software Engineering Smts (Data Science/Ml)