La descripción está en inglés, tal como la publicó la empresa.
Engagement Type: [Full-Time / Contractor]
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.
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.
Build & Maintain Scalable Data Pipelines: Develop, optimize, and maintain reliable ETL/ELT pipelines to ingest, transform, validate, and load transactional data into relational databases, particularly Microsoft SQL Server and PostgreSQL.
Support AI & Data-Driven Solutions: Contribute to data ingestion and preparation workflows that support AI applications, including document processing, metadata management, chunking, and embedding generation for Retrieval-Augmented Generation (RAG) systems.
Leverage AI-Assisted Engineering: Proactively use modern AI tools to accelerate code development, improve data transformation workflows, troubleshoot issues, and identify opportunities to make data engineering processes more efficient.
Orchestrate & Monitor Data Workflows: Develop, schedule, and monitor data processing jobs using tools such as Airflow, Azure Data Factory (ADF), and SQL Server Agent. Investigate pipeline failures and implement data quality checks to ensure reliable processing.
Improve Database & Data Model Performance: Write and optimize SQL queries, contribute to data modeling, and improve the efficiency and reliability of database operations and analytical data structures.
Collaborate & Support Production Workloads: Work alongside Senior Data Engineers, data scientists, product owners, and IT Operations to resolve production issues, implement improvements, maintain documentation, and follow established Git, Bitbucket, and Jira workflows.
Core Experience: 3+ years of professional experience in data engineering, building, maintaining, and troubleshooting data pipelines and data processing workflows in production environments.
Python & SQL Proficiency: Hands-on experience with Python, particularly for data processing and transformation, and strong SQL skills, including joins, CTEs, window functions, aggregations, and query optimization. Familiarity with pandas and experience with Microsoft SQL Server or PostgreSQL are expected.
Pipeline Orchestration & Cloud Knowledge: Practical experience developing or managing data workflows using Airflow, Azure Data Factory (ADF), or SQL Server Agent. Familiarity with cloud environments, preferably Azure, is an advantage.
Data Modeling & AI Data Preparation: Understanding of data modeling, relational database structures, and data quality principles. Exposure to document ingestion, embeddings, vector search, or data pipelines supporting AI and RAG applications is a plus.
Engineering Practices & Tools: Experience with Git-based version control, collaborative development workflows, and issue tracking tools such as Bitbucket and Jira. Familiarity with CI/CD practices and Docker is an advantage.
AI-Driven Problem Solving: A proactive mindset toward adopting AI tools to accelerate development, improve code quality, automate repetitive tasks, and solve technical challenges. Curiosity and initiative in exploring practical applications of AI in data engineering are highly valued.
Analytical Thinking & Ownership: Strong troubleshooting and problem-solving skills, attention to detail, and the ability to take ownership of assigned tasks, investigate issues independently, and collaborate effectively with senior engineers.
Communication & Collaboration: Good English communication skills, both written and verbal, with the ability to explain technical concepts clearly to cross-functional stakeholders. Ability to overlap with U.S. Central business hours is required.
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.
Explore opportunities and submit your application today!
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