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Staff Data Engineer
Robots & Pencils. Define data architecture and platform strategy across pipelines, warehouses, and data lakes .
Tech Stack
Tools & technologiesAWSCloudKafkaPythonScalaSQL
About the role
Key responsibilities & impact- Define data architecture and platform strategy across pipelines, warehouses, and data lakes
- Build and optimize scalable batch and real-time data pipelines
- Define and enforce data governance, quality standards, and compliance frameworks
- Build monitoring, logging, and alerting for data pipelines and services
- Contribute to CI/CD workflows for data deployment and automation
- Drive data platform modernization for performance, cost, and scalability
- Use AI assistants such as Claude and Cursor to improve delivery quality and speed
- Design and implement data contracts and event flows with backend, platform, and engineering teams
- Lead data pipelines for production AI/ML systems, including embeddings, vector stores, RAG preparation, feature stores, and training/inference flows
- Integrate data services with APIs, middleware, and third-party systems
- Partner with leadership on data strategy
- Collaborate with engineering, analytics, AI, and product teams
- Advocate for data quality, governance, and platform best practices
- Establish data engineering standards across the team
- Mentor junior and mid-level engineers
- Make high-stakes architectural decisions and manage long-term tradeoffs
Requirements
What you’ll need- 7+ years of professional data engineering experience, including leading complex data platform initiatives
- Strong system architecture background and expertise in distributed data systems
- Expert proficiency in Python, Scala, and SQL
- Deep expertise with cloud-native data platforms and enterprise data warehousing
- Strong experience with data pipeline orchestration and processing
- Strong experience with streaming platforms and real-time data processing, such as Kafka, Kinesis, or Pub/Sub
- Strong data modeling and data transformation experience
- Strong experience with data quality, governance, and compliance frameworks
- Strong experience with container orchestration and CI/CD for data systems
- Strong experience building data pipelines for production AI/ML systems, including embeddings, vector stores, RAG data preparation, feature stores, and training/inference data flows
- Demonstrated leadership and technical mentoring experience
- Strong stakeholder communication skills
- Demonstrable day-to-day usage and expert knowledge of AI-forward coding tools such as Claude and Cursor
- Excellent problem-solving skills and sound judgment in ambiguous technical and business challenges
- Experience with data mesh or data fabric concepts, lakehouse architectures, or governance framework implementation is a plus
- Healthcare data handling and modeling experience is a plus
- AWS certifications, such as Certified Data Engineer – Associate, are strongly preferred
- Successful completion of a background check may be required
Benefits
Comp & perks- Equal employment opportunities regardless of protected characteristics
- Employment offer may include a background check in accordance with local legislation
- Current employer will not be contacted without permission