Pika Data Engineer at Pika responsible for designing, building, and scaling data infrastructure powering the AI creative platform. The role includes developing data pipelines, ensuring data quality, and collaborating with cross-functional teams.
Responsibilities
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.
Design, develop, and maintain scalable data pipelines and ETL workflows
Build, automate, and optimize our 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
Qualification
Knowledge of database systemsFamiliarity with monitoringSelf-motivatedOpen sourcePython
Required
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
Preferred
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
