Masterworks
Overview
Data Engineer
at
Masterworks We are seeking a skilled and proactive
Data Engineer
with 2–5 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. About Masterworks
Masterworks
is a fintech platform that allows anyone to invest in SEC-qualified shares of multi-million dollar paintings by names like Banksy, Basquiat, and Picasso. In just three short years, we have built a portfolio of nearly $800 million in world-class artworks, introducing over 800,000 individuals to the $1.7 trillion art market. Masterworks has been covered by major media publications such as The New York Times, CNBC, The Wall Street Journal, and the Financial Times, and was recently recognized as one of the Top 50 Startups in the US by LinkedIn. In 2021, Masterworks achieved unicorn status raising $110M in its Series A fundraising round at a valuation exceeding $1 billion. Our 200+ employees are based out of our offices at 1 World Trade Center in the Financial District of New York City. With an entirely in-office team, there are endless opportunities for collaboration, innovation, and learning. Responsibilities
Design, build, and maintain scalable ETL pipelines using Luigi and Apache Airflow Monitor and optimize performance of Redshift clusters, including diagnosing high CPU usage, identifying slow or resource-intensive queries, and refactoring SQL for performance improvements Proactively build data quality alerts and notification systems to ensure pipeline health and catch missing/incomplete data early Collaborate with analysts and stakeholders to ensure data is accurate, available, and accessible Respond promptly to issues during working hours (within 5 minutes during core hours) Lead or assist in migration projects (e.g., Redshift to Snowflake) including planning, testing, and execution Collaborate on data modeling and schema design to support analytics and application needs Qualifications
2–5 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
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 Compensation
The compensation range for the role is
$120-180k
(base salary, exclusive of other potential benefits such as on-target earnings, bonus, and equity). Specific compensation offered may depend on education, experience, qualifications, and market data. Exceptional candidates may receive salaries outside the posted range. Seniority level
Mid-Senior level Employment type
Full-time Job function
Information Technology
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Data Engineer
at
Masterworks We are seeking a skilled and proactive
Data Engineer
with 2–5 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. About Masterworks
Masterworks
is a fintech platform that allows anyone to invest in SEC-qualified shares of multi-million dollar paintings by names like Banksy, Basquiat, and Picasso. In just three short years, we have built a portfolio of nearly $800 million in world-class artworks, introducing over 800,000 individuals to the $1.7 trillion art market. Masterworks has been covered by major media publications such as The New York Times, CNBC, The Wall Street Journal, and the Financial Times, and was recently recognized as one of the Top 50 Startups in the US by LinkedIn. In 2021, Masterworks achieved unicorn status raising $110M in its Series A fundraising round at a valuation exceeding $1 billion. Our 200+ employees are based out of our offices at 1 World Trade Center in the Financial District of New York City. With an entirely in-office team, there are endless opportunities for collaboration, innovation, and learning. Responsibilities
Design, build, and maintain scalable ETL pipelines using Luigi and Apache Airflow Monitor and optimize performance of Redshift clusters, including diagnosing high CPU usage, identifying slow or resource-intensive queries, and refactoring SQL for performance improvements Proactively build data quality alerts and notification systems to ensure pipeline health and catch missing/incomplete data early Collaborate with analysts and stakeholders to ensure data is accurate, available, and accessible Respond promptly to issues during working hours (within 5 minutes during core hours) Lead or assist in migration projects (e.g., Redshift to Snowflake) including planning, testing, and execution Collaborate on data modeling and schema design to support analytics and application needs Qualifications
2–5 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
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 Compensation
The compensation range for the role is
$120-180k
(base salary, exclusive of other potential benefits such as on-target earnings, bonus, and equity). Specific compensation offered may depend on education, experience, qualifications, and market data. Exceptional candidates may receive salaries outside the posted range. Seniority level
Mid-Senior level Employment type
Full-time Job function
Information Technology
#J-18808-Ljbffr