Masterworks
Data Engineer
We're looking for a skilled and proactive Data Engineer with 25 years of experience to help build and maintain robust, high-performance data pipelines and infrastructure. This role is ideal for someone who thrives in a fast-paced environment, has deep technical knowledge of Redshift, and is capable of diagnosing and improving SQL query performance. You'll work closely with investment advisors, engineering, product, and analytics teams to ensure the reliability, efficiency, and scalability of our data systems. Key responsibilities include: Design, build, and maintain scalable ETL pipelines using Luigi and Apache Airflow Monitor and optimize performance of Redshift clusters, particularly: diagnosing high CPU usage, identifying slow or resource-intensive queries, refactoring SQL for performance improvements Proactively build data quality alerts and notification systems to ensure pipeline health and catch missing/incomplete data early Work closely with analysts and stakeholders to ensure the data is accurate, available, and accessible Respond promptly to issues during working hours (within 5 minutes during core hours) Lead or assist in potential migration projects (e.g., Redshift to Snowflake or other tools), including planning, testing, and execution Collaborate on data modeling and schema design to support analytics and application needs Requirements include: 25 years of hands-on data engineering experience in a production environment Strong experience with Amazon Redshift, including query optimization and system diagnostics Proficiency with ETL orchestration tools such as Luigi and Apache Airflow Expert-level SQL skills; ability to analyze and optimize long-running queries Proven ability to troubleshoot high CPU or slow query issues on Redshift Familiarity with data alerting and monitoring tools (e.g., CloudWatch, Datadog, custom alert systems) Strong communication skills and a collaborative mindset High responsiveness during working hours; ability to support production data pipelines and address urgent issues quickly Experience with cloud platforms (AWS preferred) Bonus: experience leading or supporting data platform migrations Preferred qualifications include: Experience with data warehousing concepts and modern data stacks Familiarity with data pipeline logging, testing, and observability best practices Experience with Snowflake or other modern data platforms Interest in or experience with financial data or investment platforms Additional requirements: Must be eligible for full-time US work - no exceptions Must be able to work from our NY office - not a remote role Benefits: Free admission to art museums and galleries Health, dental, and vision coverage with FSA options PTO and 401k Discounted Equinox membership
We're looking for a skilled and proactive Data Engineer with 25 years of experience to help build and maintain robust, high-performance data pipelines and infrastructure. This role is ideal for someone who thrives in a fast-paced environment, has deep technical knowledge of Redshift, and is capable of diagnosing and improving SQL query performance. You'll work closely with investment advisors, engineering, product, and analytics teams to ensure the reliability, efficiency, and scalability of our data systems. Key responsibilities include: Design, build, and maintain scalable ETL pipelines using Luigi and Apache Airflow Monitor and optimize performance of Redshift clusters, particularly: diagnosing high CPU usage, identifying slow or resource-intensive queries, refactoring SQL for performance improvements Proactively build data quality alerts and notification systems to ensure pipeline health and catch missing/incomplete data early Work closely with analysts and stakeholders to ensure the data is accurate, available, and accessible Respond promptly to issues during working hours (within 5 minutes during core hours) Lead or assist in potential migration projects (e.g., Redshift to Snowflake or other tools), including planning, testing, and execution Collaborate on data modeling and schema design to support analytics and application needs Requirements include: 25 years of hands-on data engineering experience in a production environment Strong experience with Amazon Redshift, including query optimization and system diagnostics Proficiency with ETL orchestration tools such as Luigi and Apache Airflow Expert-level SQL skills; ability to analyze and optimize long-running queries Proven ability to troubleshoot high CPU or slow query issues on Redshift Familiarity with data alerting and monitoring tools (e.g., CloudWatch, Datadog, custom alert systems) Strong communication skills and a collaborative mindset High responsiveness during working hours; ability to support production data pipelines and address urgent issues quickly Experience with cloud platforms (AWS preferred) Bonus: experience leading or supporting data platform migrations Preferred qualifications include: Experience with data warehousing concepts and modern data stacks Familiarity with data pipeline logging, testing, and observability best practices Experience with Snowflake or other modern data platforms Interest in or experience with financial data or investment platforms Additional requirements: Must be eligible for full-time US work - no exceptions Must be able to work from our NY office - not a remote role Benefits: Free admission to art museums and galleries Health, dental, and vision coverage with FSA options PTO and 401k Discounted Equinox membership