Data Engineer

Location
US remote
Employment Type
Full time
Department
Engineering
OverviewApplication
About Pika
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.
About The Role
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.
What You’ll Do
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
What We’re Looking For
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
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
Our Stack
Python, Go, Node.js, Postgres, Redis, Docker, Kubernetes, AWS/GCP
What We Offer
Competitive salary in the AI industry
Substantial equity in a fast-growing startup defining the future of AI and creativity
Comprehensive health benefits, monthly stipends, and company retreats
Collaborative, high-growth culture—everyone contributes to growth and success
What You’ll Do
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
What We’re Looking For
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
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
Our Stack
Python, Go, Node.js, Postgres, Redis, Docker, Kubernetes, AWS/GCP
What We Offer
Competitive salary in the AI industry
Substantial equity in a fast-growing startup defining the future of AI and creativity
Comprehensive health benefits, monthly stipends, and company retreats
Collaborative, high-growth culture—everyone contributes to growth and success
What You’ll Do
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
What We’re Looking For
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
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
Our Stack
Python, Go, Node.js, Postgres, Redis, Docker, Kubernetes, AWS/GCP
What We Offer
Competitive salary in the AI industry
Substantial equity in a fast-growing startup defining the future of AI and creativity
Comprehensive health benefits, monthly stipends, and company retreats
Collaborative, high-growth culture—everyone contributes to growth and success

Work arrangement
Yes