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Job Overview
Location
Remote
Job Type
Full-time
Category
Software Engineering
Date Posted
September 20, 2025
Full Job Description
đź“‹ Description
- • Own the end-to-end design, build, and optimization of petabyte-scale batch ETL/ELT pipelines that power real-time analytics and machine-learning models for US-based enterprise clients.
- • Architect and govern a cloud-native lakehouse on AWS S3 using Apache Iceberg—define partitioning strategies, evolve schemas without downtime, and automate compaction & snapshot retention to balance cost and performance.
- • Develop distributed data-processing jobs in PySpark, tuning caching, serialization, and resource allocation to cut EMR spend by double-digit percentages while meeting strict SLA windows.
- • Create resilient Airflow DAGs with smart retry logic, backfill strategies, and metadata-driven scheduling that reduce on-call alerts and free the team for innovation.
- • Embed data-quality gates, anomaly detection, and row-level security directly into pipelines; leverage AWS Glue Catalog, Lake Formation, and IAM fine-grained policies to guarantee compliance with SOC-2 and HIPAA requirements.
- • Champion software-engineering best practices: trunk-based Git workflows, peer reviews, automated testing with pytest, and CI/CD pipelines that deploy new Spark jobs to EMR in minutes with zero downtime.
- • Partner with data scientists, product managers, and business stakeholders to translate vague requirements into scalable data products; prototype rapidly with GitHub Copilot and other AI assistants, then harden for production.
- • Continuously evaluate emerging tech—be the first to run benchmarks on Spark 4.0, test new Iceberg features, or pilot AWS Athena engine v3—sharing findings through internal tech talks and concise design docs.
- • Mentor junior engineers via pair programming and code labs; foster a blameless culture where post-mortems lead to actionable improvements and shared ownership of the data platform.
- • Monitor cost, performance, and data-drift through CloudWatch, Prometheus, and custom dashboards; set auto-scaling policies that keep compute spend predictable while absorbing peak loads.
- • Participate in a lightweight, feedback-driven agile process: daily async stand-ups, bi-weekly demos, and quarterly OKRs that align personal growth with company revenue targets.
- • Represent Nearsure’s remote-first culture by communicating proactively across time zones, documenting decisions in English, and celebrating team wins during virtual coffee breaks or LATAM coworking days.
🎯 Requirements
- • 5+ years designing and operating large-scale data pipelines, with expert-level Python and SQL skills.
- • 3+ years hands-on experience with Apache Spark (PySpark) and 2+ years building lakehouse architectures with Apache Iceberg on AWS S3.
- • 2+ years production usage of AWS EMR, Athena, Glue, Lambda, and Airflow; solid grasp of IAM, VPC, and cost-optimization levers.
- • Advanced English (C1+) for daily client interaction, technical documentation, and incident calls.
🏖️ Benefits
- • 100 % remote work from anywhere in LATAM with flexible hours and a monthly refundable credit for coworking, gear, or wellness.
- • Competitive USD salary paid bi-weekly, plus 15+ PTO days, local holidays, and a birthday off to recharge with loved ones.
- • Career accelerator: dedicated training budget, English classes, internal tech talks, and paid certifications (AWS, Databricks, Confluent, etc.).
Skills & Technologies
About Nearsure LLC
Nearsure LLC is a U.S.-based technology services company offering nearshore software development and staff augmentation across Latin America. Founded in 2018, it delivers remote engineering teams specializing in web, mobile, cloud, AI/ML, and data solutions for North American clients seeking cost-effective, time-zone-aligned talent. The company employs 500+ engineers across 18 countries, operates fully distributed, and is headquartered in Palo Alto, California.
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