Data Operations Analyst

We’re searching for a Data Operations Analyst to join our high-performing team responsible for upholding world-class data quality across our product and analytics environments. Our success—and our ability to innovate—hinges on having clean, reliable data readily available to the entire organization. When data is accurate and trustworthy, we can confidently make decisions, develop cutting-edge AI solutions, and offer unparalleled insights to our customers. In this role, you will be a data analyst and detective owning the operational heartbeat of our data processes, overseeing recurring processes to uncover potential improvements, collaborating with Engineering and Data Science on solutions, and continuously refining workflows for efficiency and scale. You have a keen eye for detail and are willing to go deep root-causing when the data doesn’t align with expectations. You’ll follow standard operating procedures (SOPs), service-level agreements (SLAs), and other best practices that elevate the team’s performance and ensure seamless cross-functional collaboration. If you want to help define the next generation of data-powered products in a massive industry, this is the perfect opportunity for you. Expect autonomy in your work, support from a team that values continuous learning, and the chance to directly shape our solutions and strategy. Project is a leading New York-based data and AI software specializing in the $2.3 trillion dollar building materials industry. Our platform, powered by advanced Machine Learning and Artificial Intelligence, provides manufacturers with a data-driven approach to better service customers and grow their relationships with key accounts. By simplifying massive datasets into actionable business insight, we help businesses make data-driven decisions to optimize pricing, inventory, and product assortment. Our values - We value execution: momentum is everything - Belief in the power of positivity: we are encouraging and take risks - Proactive ownership: we are passionate about driving financial value with a creative data product - Foster collaboration: we welcome help and always extend a helping hand, internally and externally Requirements - Education: Bachelor's degree in a technical field (e.g., Industrial Engineering, Information Systems) or equivalent practical experience in a data-heavy environment. - Experience: 1–3 years of experience as a QA Analyst, Data Analyst, or similar role. - Technical Proficiency: Strong proficiency in SQL and familiarity with data warehousing solutions (e.g., Snowflake, Google BigQuery, ClickHouse). - Coding: Experience cleaning and normalizing key data sources using SQL and Python. - Visualization: Experience building and using data visualization tools (e.g. Hex, Preset, Tableau) is a plus. - Math & Stats: An understanding of statistical measurements of accuracy (e.g., correlation, variance). - Automation: Experience identifying and executing operational improvements through automation. Who You Are (Attributes) - An Owner: You maintain an attitude of ownership of your work and adopt strong organizational skills. - A Self-Starter: You adopt a self-starter mentality and inspire other team members to do the same. - A Collaborator: You possess effective communication and collaboration skills, with the ability to work well in a team environment. - A Clear Communicator: You are adept at clear, concise written and verbal communication, comfortable interacting with both technical and non-technical audiences. - Resilient: You have the ability to prioritize tasks and manage time effectively in a fast-paced environment. Responsibilities - Be the Data Detective: Perform root cause analysis using SQL and Python to uncover nuances and issues with the data, ensuring nothing slips through the cracks. - Drive Quality Assurance: Conduct QA procedures and regular backtesting processes to pinpoint opportunities for enhancing data accuracy and consistency. - Engineer Automated Solutions: Identify process improvements through automation and work hand-in-hand with Engineering teams to build automated solutions. - Optimize Data Pipelines: Clean and normalize key data sources and collaborate with Engineering to refine systems, ensuring data flows smoothly from source to destination. - Visualize Health: Build data visualizations that support you and your teammates’ day-to-day QA workflows. Communicate & Align: Communicate updates and progress to Product, Analytics, and other stakeholders, ensuring alignment on priorities and timelines. Work conditions - Opportunities to work on diverse and challenging projects. - A supportive and collaborative team environment. - 12 vacation days per year. - 5 sick days per year. - English classes. - Access to therapist and psychologist support for mental well-being.