Sierra is building out its core data foundations and needs to shape the company's data strategy and infrastructure to enable AI-powered customer interactions.
Requirements
- Strong proficiency in SQL and Python
- expertise in distributed data processing frameworks (e.g., Spark, Flink, Kafka)
- expertise in cloud-based platforms (AWS, GCP)
- Deep experience with data modeling, warehousing, and designing schemas optimized for analytics, experimentation, and AI/ML workloads
- Strong understanding of data validation, monitoring, compliance, and best practices for ensuring data integrity across pipelines
- Experience with (open to equivalents) - AWS Glue, Athena, Kafka, Flink/Spark, dbt, Airflow/Dagster, Terraform
- Experience working with large language models (LLMs), conversational AI, or agent-based systems
Responsibilities
- design and operate scalable batch and real-time data systems
- create trusted data models
- build the pipelines that power experimentation, analytics, and AI development
- ensure that every area of the business—from customer experience to go-to-market execution—has access to high-quality, reliable data to drive insight and innovation
- influence how data is captured, governed, and leveraged across Sierra, empowering decision-making at scale
- establish the foundations of Sierra’s data ecosystem
- drive standards for reliability and trust
Other
- Proven Experience: Extensive experience in data engineering, with a track record of designing and operating data pipelines, systems, and models at scale.
- Curiosity & Customer Obsession: Passion for building trustworthy data systems that empower teams to better understand users and deliver impactful product experiences.
- Adaptability and Resilience: Comfort working in a fast-paced startup environment, able to adapt to evolving priorities and deliver reliable solutions amidst ambiguity.
- Excellent Communication: Ability to translate technical infrastructure and data design trade-offs into clear recommendations for product, engineering, and business stakeholders.
- Great Collaboration: Proven ability to partner closely with product, ML, analytics, and GTM teams to deliver data foundations that unlock business and product innovation.
