岗位大厅/Data & analytics/Data Engineer

Pika · 53天前 · 来源 ATS 官方

Data Engineer

US remote办公方式未标注
全职Data & analytics
薪资未披露

🛡 岗位真实性核验

Ghost Job 检测

🛡 申请链接 核验有效

信号由后台自动核验生成,仅供参考;判断权在你。设计案:GHOST-JOB-P1

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必备技能

AIAWSAirflowAnalyticsBigQueryCloudDagsterData EngineeringData ModelingData Pipelines

免费注册后解锁"你的匹配分 vs 高分画像"与个人技能缺口。

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职位描述

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

🈯 翻译这份 JD · 红灯 0 / 黄灯 2 / 绿灯 1点开 ▾
可以投——没有红灯,黄灯问题放进面试清单问清即可。
fast-paced → 流程不成熟、需求常变要问的问题:「节奏快」的交付周期是多久?需求由谁定?
competitive salary → 形容词,不是数字要问的问题:这个岗位的预算范围是多少?
nice to have → 加分项,不是门槛
词典只标"常见信号",不对公司下结论——红灯 = 面试里该当面确认的问题。想自己翻别的 JD:JD 翻译器 →
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公司 · Company

Pika

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US remote来源:ATS 官方

⚑ 岗位信息收录自公开招聘页(ATS 官方),以雇主官网为准