About the role
Engagement Type: Contractor (100% Remote, Latin America)
About CodeRoad
CodeRoad is a technology execution partner trusted by companies across North America since 2002. We work alongside our clients to engineer, modernize, and scale the technology that powers their businesses, combining deep technical expertise, specialized teams, and shared accountability for outcomes. Our capabilities span product engineering, platform engineering, legacy modernization, and AI engineering.
Our engineers, designers, delivery leaders, and technology specialists collaborate through Velocity Studios: specialized teams developed within CodeRoad to deliver complex technology initiatives. Being assigned to a project means you become part of a collaborative environment where you can strengthen your expertise, take ownership of meaningful work, and grow alongside experienced professionals.
Why Build Your Career at CodeRoad?
- High-Velocity Work & Client Exposure: We work close to the technology, teams and roadmaps that move real outcomes. Direct engagement with U.S. client teams and roadmaps.
- Career Continuity & Long-Term Opportunity: Your career here can outlast any single project. Continuous multi-project pipeline; long-tenure CodeRoaders.
- Engineering Autonomy & Technical Mastery: We invest in the skills that shape what's next. Agentic AI tools and training, Coursera Enterprise, Studio practice labs, L1-L7 Career Framework.
- High-Trust Employee Experience: You grow in an environment built on trust, transparency and recognition. High-touch onboarding, transparent leadership communication, community recognition, psychological safety.
Key Responsibilities
- Architect & Scale Robust Pipelines: Design, build, and maintain high-performance batch and real-time streaming data pipeline architectures that ingest, process, and deliver large, complex datasets reliably.
- Drive Automation & System Reliability: Identify opportunities to automate manual workflows, optimize query execution, and re-engineer cloud infrastructure to enhance data freshness, scalability, and system fault tolerance.
- Modernize Cloud Data Infrastructure: Build production-grade ETL/ELT pipelines using Python, SQL, and enterprise cloud ecosystems (Azure / GCP) to extract and unify data across distributed sources.
- Empower Analytics & AI Initiatives: Develop, test, and maintain tailored data tooling, data marts, and feature stores that enable analytics engineers and data scientists to deploy performant models and business intelligence solutions.
- Take Technical Ownership: Collaborate directly with cross-functional stakeholders in North America, leading root cause analysis on pipeline bottlenecks, managing dependencies, and ensuring sound data governance across environments.
What You Bring
- Proven Engineering Track Record: 4+ years of professional experience in data engineering, with proven expertise in data modeling, metadata management, and workload orchestration.
- Core Technology Mastery: Advanced proficiency in Python and complex SQL; hands-on production experience with Databricks (Scala experience is a strong plus).
- Big Data & Cloud Tooling: Practical experience with distributed processing engines like Apache Spark, paired with cloud data platforms such as Azure Data Factory, Azure Synapse, or Google BigQuery.
- Modern Pipeline Delivery: Solid track record architecting both stream-based and batch-oriented data pipelines capable of handling semi-structured and unstructured data at scale.
- Consultative Mindset & Communication: Advanced English proficiency (B2+/C1) with exceptional written and spoken communication skills, comfortable driving technical conversations with U.S.-based engineering teams aligned to East or West Coast business hours.
What You’ll Love
- USA Contractor / 100% Remote
- Competitive Pay (USD)
- Holidays Off & Paid Time Off
- Health insurance assistance program
- Opportunity to work with high-growth US-based companies and cutting-edge tech stacks.
Ready to Build What Actually Ships?
Explore opportunities and submit your application today!