Senior Data Engineer at Red Hat designing and optimizing 데이터 솔루션 supporting sales and forecasting. Collaborating with teams and applying modern data engineering practices to ensure data quality.
About the role
- Senior Data Engineer leading the Data Engineering program for generative AI technology at Docuvera. Design and build scalable data foundations while ensuring data quality and security compliance.
Responsibilities
- Set up and lead our Data Engineering program: the platform, the standards, the culture, and the momentum.
- Design and build the data foundations that power our natural language + generative AI features.
- Own end-to-end delivery, partner closely with product/engineering/customer teams.
- Help us ship complex solutions for international customers — reliably, securely, and at scale.
- Build batch + streaming pipelines for multi-client document ingestion at scale using Apache Iceberg on S3, exposed natively into Snowflake.
- Set up data quality + observability to ensure we don’t repeat the same issues.
- Ensure data security compliance with GDPR, data residency, IAM least privilege, etc.
- Help build a high-performing Data Engineering function: standards, mentoring mid-level engineers, CI/CD for pipelines, infrastructure-as-code practices.
- Design and maintain Snowflake data models for analytics + ML consumption.
Requirements
- Strong hands-on AWS experience: S3, Glue, Kinesis, Lambda, SQS, IAM, CloudWatch
- Deep Snowflake experience: schema design, performance tuning, streams + tasks, clustering, masking + row-level security
- Solid experience with Apache Iceberg in an S3-based lake setup, including exposing Iceberg tables to Snowflake (external tables or native Iceberg support)
- Advanced SQL + strong dbt/ELT design skills, and real-world batch/streaming experience (late data, at-least-once delivery, etc.)
- Kimball dimensional modelling know-how (facts/dims, SCD Type 1/2/3, conformed dimensions) in Snowflake
- IaC + CI/CD experience (Terraform or AWS CDK), plus familiarity with observability tools like Great Expectations / Monte Carlo (or similar)
- Experience supporting ML + GenAI data needs: feature stores, embedding pipelines, SageMaker integration, RAG-friendly data engineering
- Good grasp of multi-region governance/compliance: right-to-erasure, residency enforcement, audit logging, secrets management
- Comfortable leading: setting standards, mentoring, and explaining trade-offs clearly to non-technical stakeholders.
Benefits
- Work your way. We’re digital-first and fully flexible, with asynchronous work as the norm.
- Our New Zealand offices in Wellington and Palmerston North are always open; come for the snacks, drinks and table tennis, stay for the great people and connection.
- Pride in what we do. There's nothing like joining a tech scale-up that's highly regarded on the world stage where what we do makes a tangible difference in the world.
- Modern tools that work for you. As an AI-agentic company, we use the latest systems and tools to make work smarter.
- Space to grow. You’ll have access to learning and development resources, plus dedicated tools-down time for personal growth.
- Time to recharge. In New Zealand, enjoy an extra week of paid leave; time off over Christmas, and your birthday off. In the U.S., we offer unlimited PTO and funded health benefits, including dental and medical.
- A close-knit global team. You’ll be part of a dedicated, collaborative community that stays connected no matter where you’re based.
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