AI Summary
Design and develop production-grade pipelines, leverage GenAI tools, and define engineering best practices. Collaborate with cross-functional teams and mentor junior engineers. Implement robust data quality, testing, and governance frameworks.
Key Highlights
Design and develop end-to-end data pipelines
Leverage GenAI tools (Copilot, Claude, Gemini) for productivity
Implement robust data quality, testing, and governance frameworks
Mentor junior engineers and contribute to capability building
Collaborate with cross-functional teams
Technical Skills Required
Benefits & Perks
Competitive compensation
Flexible work arrangements
Professional development support
Cloud certification sponsorship
Job Description
Description
AuxoAI is seeking a Senior GenAI Data Engineer with strong fundamentals in data engineering and end-to-end solution design. In this role, you will design and develop production-grade pipelines, leverage GenAI tools (Copilot, Claude, Gemini) to boost development productivity, and define engineering best practices across complex data environments. This is a highly collaborative, cross-functional role ideal for someone who thrives at the intersection of data engineering excellence and GenAI-powered :
- Architect and develop end-to-end data pipelines from ingestion to transformation to consumption
- Lead solutioning and integration for complex data workflows (batch and streaming)
- Use AI-assisted coding tools (e.g., GitHub Copilot, Claude, Gemini) to accelerate code development, refactoring, and debugging
- Implement robust data quality, testing, lineage, and governance frameworks
- Drive best practices across pipeline performance, reusability, and scalability
- Mentor junior engineers and contribute to capability building within the data team
6+ years of experience in data engineering, with expertise in :
- End-to-end pipeline development (batch and streaming)
- Data modeling (dimensional, Data Vault, OBT)
- ETL/ELT design patterns, performance tuning, and optimization
- SQL (Advanced) and Python (Advanced)
- Apache Spark for large-scale data processing
- Proficiency using AI coding tools (e.g., Copilot, Claude, Gemini) to enhance productivity and code quality
- Strong understanding of data quality frameworks, unit testing, and CI/CD for data workflows
- Experience with Google Cloud Platform services : BigQuery, Dataflow, Cloud Composer, Pub/Sub, Dataproc, Vertex AI
- Exposure to finance or sales data domains
- Familiarity with Databricks, Delta Lake, or Apache Iceberg
- GCP Professional Data Engineer certification is a plus
- Opportunity to work on modern data platforms with GenAI integration
- Access to professional development support and cloud certification sponsorship
- Competitive compensation and flexible work arrangements
- A fast-paced, high-impact environment where innovation is valued