Senior Big Data Engineer – AI Data Systems (Remote)
Location: Remote
Employment Type: Contract / Remote
Industry: Artificial Intelligence & Data Engineering
Role Summary
Are you a Big Data Engineer ready to shape the future of artificial intelligence? We are seeking a contract Senior Big Data Engineer to build high-throughput data architectures and scalable ETL pipelines that directly power next-generation AI and machine learning models.
In this role, you will design distributed processing systems, optimize complex database infrastructures, and enable AI models to learn from high-quality, real-world data at scale.
Key Responsibilities
Scalable Architecture: Design, deploy, and maintain large-scale distributed data pipelines and cloud architectures supporting AI systems.
Pipeline Development: Build robust ETL/ELT data integration, transformation, and processing workflows using Python and modern big data frameworks.
Database Optimization: Manage, optimize, and scale relational and NoSQL databases, ensuring fast query performance and high availability.
System Health & Performance: Proactively monitor, troubleshoot, and fine-tune distributed systems to maintain minimal latency and peak performance.
Governance & Security: Enforce strict data governance, quality assurance, and end-to-end security protocols across all pipelines.
Technical Communication: Document data solutions clearly and collaborate across teams to align engineering deliverables with business goals.
Required Qualifications
Big Data Expertise: Extensive hands-on experience designing and optimizing large-scale, enterprise data architectures.
Python Mastery: Advanced proficiency in Python for data pipeline automation, integration, and complex backend scripting.
Distributed Computing: Practical experience with frameworks like Apache Spark, Hadoop, or Flink.
Data Management: In-depth knowledge of data modeling, ETL design, and management of both relational and NoSQL storage engines.
Communication: Ability to distill complex, technical concepts for both engineering teams and business stakeholders.
Remote Leadership: Self-directed and proactive, with a track record of thriving in dynamic, fully remote settings.
Preferred Qualifications
Experience with major cloud platforms (AWS, GCP, or Azure).
Familiarity with Machine Learning Operations (MLOps) and data science integration workflows.
Prior experience supporting global teams within high-growth tech environments.