Staff Engineer – Data Engineering

🕒 May 1

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Logo of Chartbeat

Chartbeat

51 - 200 employees

Founded 2009

📱 Media

☁️ SaaS

💰 $7M Venture Round on 2018-07

Media • Analytics • SaaS

Chartbeat is a company that provides powerful software solutions for media companies, enabling them to optimize content, grow loyal audiences, and enhance strategies through insightful analytics. The company's tools, such as Chartbeat for Publishing and Datastream, offer real-time data and insights, allowing editorial and marketing teams to make informed decisions rapidly. Chartbeat is trusted by thousands of content teams globally, providing real-time monitoring and analytics to improve engagement and usability. The platform is especially beneficial for newsrooms, editorial brands, and marketing needs, helping to consistently optimize content strategy and execution.

📋 Description

• Design, own and contribute to the cross-division data architecture, establishing patterns and standards that scale across both Chartbeat and Tubular platforms • Lead the technical strategy for integrating data products across divisions, enabling new cross-brand features and insights • Drive the AI and backend infrastructure roadmap - from data pipelines that feed models to deployment patterns for LLM-powered features • Identify and close skill gaps across the data engineering team, actively mentoring engineers and elevating the collective technical ceiling • Collaborate with product, engineering, and ML teams to translate business needs into scalable architectural decisions • Establish and evolve best practices for data modeling, pipeline design, and system observability across the organization • Evaluate and prototype emerging AI and generative AI technologies for application to real-world product challenges • Participate in engineering planning and contribute to roadmap prioritization with a cross-division perspective • Be part of engineering on call rotation to monitor and maintain the health of our production systems.

🎯 Requirements

• 8+ years of experience in data engineering, data architecture, or a closely related discipline • Proven experience designing large-scale data systems across complex, multi-product or multi-division environments • Strong proficiency with cloud data warehouse technologies (Snowflake, BigQuery, or equivalent) • Experience building and maintaining data pipelines at scale, streaming and batch, using tools such as Kafka, Spark, Airflow, or similar • Demonstrated experience integrating AI and ML capabilities into data systems, including LLMs or foundation models in production environments • Strong Python and Data Architecture experience • Excellent communication skills - able to translate complex architectural decisions for both technical and non-technical audiences • A track record of elevating engineering teams through mentorship, documentation, and technical leadership • Experience with Kubernetes or containerized infrastructure is a plus

🏖️ Benefits

• Comprehensive Health, Dental, and Vision Insurance • 401K with company match (100% of the first 3% and 50% of the next 2%) • Fully Paid Parental Leave - 18 weeks for birthing parents, 12 weeks for non-birthing parents • Phone and internet stipend • Wellness, learning, and coworking reimbursements • Flexible work hours • Unlimited PTO • 11 paid holidays and December holiday closure • Annual In-Person Event

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