Pika is hiring a Data Engineer (hybrid) in Palo Alto, CA to design, build, and scale the data infrastructure behind its creative AI platform.

Design, develop, and maintain scalable data pipelines and ETL workflows
Build, automate, and optimize the data infrastructure used for analytics, reporting, and machine learning applications
Maintain data quality, consistency, and security across all sources and sinks
Partner with engineering, analytics, and product teams to define data requirements and deliver reliable datasets
Implement monitoring and proactively resolve data pipeline issues
Optimize storage and data processing performance as usage and scale grow
Contribute to data modeling and schema design for analytics and product needs
Help establish data engineering best practices and support a data-driven culture across the organization

4+ years of experience as a data engineer or in a similar role building and maintaining data infrastructure
Strong software engineering background with proficiency in Python, SQL, and/or similar languages
Hands-on experience with data pipeline orchestration tools: Airflow, Prefect, Dagster, etc.
Experience with cloud data platforms such as AWS/GCP, Redshift, BigQuery, Snowflake, etc.
Knowledge of database systems, data modeling, and data warehousing best practices
Familiarity with monitoring, logging, and data quality practices for data workflows
Excellent analytical and problem-solving skills with strong attention to detail
Strong communication skills and ability to work cross-functionally
Self-motivated, curious, and comfortable working in a fast-paced, high-growth startup environment

Competitive salary in the AI industry
Substantial equity in a fast-growing startup focused on AI and creativity
Comprehensive health benefits, monthly stipends, and company retreats
Collaborative, high-growth culture where everyone contributes to growth and success

Experience supporting data for machine learning or AI-powered applications
Familiarity with real-time or streaming data architectures (Kafka, Kinesis, etc.)
Prior work at high-growth startups or experience with rapid scaling
Open source, hackathon, or data engineering community experience

Data Engineer

Job Description