Data Engineer

At Pika, we’re building the next generation of AI creative tools to empower human creativity. Our mission is to make video creation seamless, intuitive, and accessible to everyone, leveraging the power of advanced AI. We believe that AI should amplify creative expression—enabling everyone to create, collaborate, and communicate across media. Our team includes engineers, artists, and product thinkers, all passionate about building tools that unlock new creative possibilities.

Pika has raised significant funding and is backed by leading investors, with a collaborative culture based in Palo Alto, CA. We prefer hybrid in-office, sharing ideas and launching products together.

We are seeking a Data Engineer to design, build, and scale the data infrastructure powering Pika’s creative AI platform. As a Data Engineer, you will play a key role in architecting, implementing, and maintaining our data pipelines and analytics systems, enabling our team to make data-driven decisions and deliver world-class AI experiences. You will work closely with product, engineering, and data teams to ensure data is accurate, reliable, and accessible for users and internal business needs.

You will combine software engineering know-how with data architecture expertise, helping us build robust, scalable, and high-performance systems. Your contributions will directly support the success of millions of creators and help shape the future of AI-powered media tools.

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  Design, develop, and maintain scalable data pipelines and ETL workflows

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  Build, automate, and optimize our data infrastructure for analytics, reporting, and machine learning applications

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  Ensure data quality, consistency, and security across all sources and sinks

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  Collaborate with engineering, analytics, and product teams to define data requirements and deliver reliable datasets

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  Implement monitoring solutions and proactively resolve data pipeline issues

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  Optimize storage and data processing performance for growth and efficiency

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  Contribute to data modeling efforts and schema design for analytics and product needs

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  Help establish best practices and empower a data-driven culture across the organization

• 4+ years of experience as a data engineer or in a 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

• 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

Python, Go, Node.js, Postgres, Redis, Docker, Kubernetes, AWS/GCP