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Pika is building next-generation AI creative tools to empower human creativity, with a focus on making video creation seamless and accessible. The company is well-funded, backed by leading investors, and based in Palo Alto with a collaborative hybrid culture.
As a Data Engineer, you will design, build, and scale the data infrastructure powering Pika's creative AI platform. You'll play a key role in architecting, implementing, and maintaining data pipelines and analytics systems that enable data-driven decision-making and world-class AI experiences. Working closely with product, engineering, and data teams, you'll ensure data is accurate, reliable, and accessible for both users and internal business needs.
Key responsibilities include:
- Design, develop, and maintain scalable data pipelines and ETL workflows
- Build, automate, and optimize data infrastructure for analytics, reporting, and machine learning applications
- Ensure data quality, consistency, and security across all sources and sinks
- Collaborate with engineering, analytics, and product teams to define data requirements and deliver reliable datasets
- Implement monitoring solutions and proactively resolve data pipeline issues
- Optimize storage and data processing performance for growth and efficiency
- Contribute to data modeling efforts and schema design for analytics and product needs
- Help establish best practices and empower a data-driven culture across the organization
You'll combine software engineering expertise with data architecture knowledge to build robust, scalable, and high-performance systems. Your contributions will directly support millions of creators and help shape the future of AI-powered media tools.
Tech stack: Python, Go, Node.js, Postgres, Redis, Docker, Kubernetes, AWS/GCP.
REQUIREMENTS:
- 4+ years of experience as a data engineer or similar role designing, 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 (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 attention to detail
- Great communication skills and ability to work cross-functionally in a collaborative environment
- Self-motivated, curious, and comfortable in a fast-paced, high-growth startup
NICE TO HAVE:
- 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
