Data Engineer

**About the Role** We’re looking for a Senior Data Engineer to help build, scale, and improve the data infrastructure at the heart of Chartmetric. Our customers depend on the data that we collect, process, and analyze from music streaming platforms, social networks, radio, charts, and more to make important business decisions, and our new AI products create even greater opportunities to make it useful. In this hands-on engineering role, you’ll work closely with our data engineering, backend, and product teams and design reliable data pipelines, investigate the underlying causes of failures, improve processing performance, and build better solutions to make our infrastructure more scalable and cost-efficient. We're looking for someone who enjoys understanding how systems actually work, challenges existing assumptions, and takes pride in making complex data infrastructure simpler, faster, and more reliable. **What you'll do** * **Build and optimize data pipelines.** Design, maintain, and scale reliable systems for ingesting, transforming, and processing large volumes of data from diverse sources. * **Improve performance and reliability.** Identify bottlenecks, optimize queries and storage, and build monitoring and validation systems to maintain data quality and prevent recurring failures. * **Own data infrastructure.** Improve databases and cloud infrastructure, leveraging technologies such as PostgreSQL, ClickHouse, and AWS to support growing data volumes efficiently. * **Power analytics and AI products.** Build the data foundations behind Chartmetric’s dashboards, APIs, and AI-native experiences, including Chartmetric Flow. * **Solve complex technical problems.** Debug production issues, investigate root causes, and develop durable solutions in collaboration with backend, product, and data engineering teams. * **Drive engineering excellence.** Use AI-assisted development tools to improve productivity while contributing to code reviews, documentation, best practices, and team knowledge sharing. * This position is **hybrid** , in our San Mateo or New York office 3–4 days a week **Qualifications** * 2–4 years of experience building production data pipelines, preferably in high-volume consumer or entertainment industries * Strong Python and SQL, with hands-on experience in Apache Airflow (or a similar orchestrator), a columnar warehouse such as ClickHouse or Snowflake, and AWS. Experience with modern analytical databases, cloud infrastructure, and orchestration tools is particularly valuable. * Experience building and running pipelines that handle millions of records a day, including messy third-party APIs (rate limits, retries, changing schemas) * Strong communication skills, able to work well with engineers across different disciplines. You're comfortable explaining technical tradeoffs, challenging assumptions constructively, and collaborating with a distributed team. * Bachelor's degree in Computer Science, Data Engineering, or equivalent practical experience * Thrives in dynamic startup environments with rapidly evolving requirements and tight delivery timelines * Bonus: Experience with music industry data, streaming APIs, or social media analytics platforms **Why Chartmetric** You’ll help shape the engineering organization behind a profitable global business, with direct access to the founder and a clear connection between your work and customer outcomes. Our challenges span large-scale data collection, analytics, product development, and new AI experiences. You’ll have room to improve an established platform while helping the team build what comes next, and benefiting from the following and more: * Competitive salary and equity package * Stipends for health & wellness, streaming services, live music events, and more * Comprehensive health, dental, and vision insurance * Real ownership of pipelines that customers use every day * Access to cutting-edge tools and technologies **Team Culture** We believe that great developer experiences lead to better products and happier teams. Our Data Engineering team operates as enablers and force multipliers, working collaboratively to remove friction from the development process. We value automation, measurement, and continuous improvement, always asking "how can we make this better for our engineering team and ensure quality data to form insights?"