About the Role

Were seeking a Technical Operations Engineer who will take ownership of ensuring the stability, scalability, and reliability of complex data pipelines and infrastructure. This role is highly autonomous and hands-on, requiring someone who thrives in a fast-paced, collaborative environment, with strong expertise in Python, cloud platforms, and data operations.

Youll work across teams to operationalize data architectures, optimize pipelines, and deliver robust solutions that drive both internal efficiency and customer satisfaction.

What Youll Be Doing

Operational Reliability: Own and ensure the health, stability, and performance of AI-driven data platforms, pipelines, and infrastructure.
Pipeline Optimization: Monitor, troubleshoot, and optimize complex ETL/ELT workflows, ensuring data quality and availability.
Automation: Develop Python-based scripts and tools to automate deployments, workflows, and system maintenance.
Advanced Support: Collaborate with Engineering, Product, and Customer Success to resolve complex operational issues and ensure seamless data delivery.
Documentation: Build and maintain detailed operational runbooks, incident playbooks, and system guides.
Collaboration: Work in an Agile environment with engineers, product managers, and data scientists to operationalize analytics for Life Sciences & Healthcare datasets.

What You Bring

Bachelors or Masters in Computer Science, Engineering, or related field.
4+ years in Technical Operations, DevOps, or SRE with focus on data platforms.
Proven experience managing enterprise-grade data services (Data Pipelines, Data Lakes, Warehouses).
Expert Python skills for automation and operational tooling.
Strong cloud experience (AWS or GCP) including compute, storage, databases, containerization, orchestration.
SQL proficiency with BigQuery, Redshift, or Snowflake.
Deep knowledge of ETL/ELT best practices, data governance, and compliance.
Ability to diagnose complex distributed systems issues with strong RCA skills.
Excellent communication (verbal & written) and experience creating technical documentation.
Collaborative, proactive mindset with strong ownership.
Ability to work with stakeholders in EST timezone.
Experience in regulated industries (healthcare, finance) and compliance (HIPAA).

Nice to Have

Experience in Life Sciences / Healthcare data domain.
Knowledge of MLOps and deploying AI/ML models.
Familiarity with data visualization tools (Looker, PowerBI, etc.).
Experience with Elasticsearch or search technologies.
Understanding of ML frameworks (TensorFlow, PyTorch, Scikit-learn, MLFlow).

What Darwoft Offers

Contractor agreement with payment in USD
100% remote work
Argentinas public holidays
English classes
Referral program
Access to learning platforms

Technical Operations Engineer

LATAM

Remote

Senior

Darwoft