YipitData, a market research and analytics firm focused on the disruptive economy, most recently secured $475M in funding from The Carlyle Group at a valuation exceeding $1B. The company's proprietary technology processes billions of alternative data points daily to surface insights across sectors such as software, AI, cloud, e-commerce, ridesharing, and payments. Its data and research teams convert raw data into strategic intelligence, providing accurate, timely, and deeply contextualized analysis for clients ranging from major investment funds to Fortune 500 companies. Offices are located in the US (NYC, Austin, Miami, Mountain View), APAC (Hong Kong, Shanghai, Beijing, Guangzhou, Singapore), and India. The company's culture, recognized by Inc. as a Best Workplace for three consecutive years, focuses on transparency, ownership, and continuous mastery. This is a remote opportunity based in India. During training and onboarding, several hours of overlap with US working hours are expected. After that, standard IST working hours apply, with the exception of 1-2 days per week for meetings with the US team. We are looking for a Data Engineer to join the Data Engineering team. The ideal candidate should have 4-7 years of data engineering experience along with a solid understanding of Spark, PySpark, and SQL, and experience with data pipelines. The hired individual will help build out the data engineering team to support a strategic pipeline and optimize for reliability, efficiency, and performance. Data Engineering serves as the gold standard for all other YipitData analyst teams by building and maintaining the core pipelines and tooling that power their products. This is a unique opportunity to be the first hire in the team, with the potential to build and lead the team as responsibilities expand. Responsibilities include: reporting directly to a Manager of Data Engineering who will provide hands-on training on data tools and techniques; building and maintaining end-to-end data pipelines; helping set best practices for data modeling and pipeline builds; creating AI-ready analytical datasets with structure, metadata, documentation, and business context for use by AI agents and insight-driven applications; solving complex data pipeline issues using PySpark and SQL; collaborating with stakeholders to incorporate business logic into central pipelines; and learning Databricks, Spark, AI, and other internally developed ETL toolings. Candidates are likely to succeed if they hold a Bachelor's or Master's degree in Computer Science, STEM, or a related technical discipline; have 4+ years of experience as a Data Engineer or in other technical functions; are motivated by data challenges and learning new skills; have strong understanding of working with data or building data pipelines; are comfortable with large-scale datasets using PySpark, Delta, and Databricks; understand business needs and the rationale behind data transformations; are eager to learn new technologies; are a self-starter who enjoys collaborative work with stakeholders; and have strong verbal and written communication skills. Nice to have: experience with Airflow, dbt, Snowflake, or equivalent. Benefits include a competitive salary, comprehensive benefits, perks, vacation time, parental leave, team events, learning reimbursement, and more. Growth at YipitData is determined by impact rather than tenure, unnecessary facetime, or office politics. Everyone is empowered to learn and master their skills in an environment focused on ownership, respect, and trust. YipitData is committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, marital status, disability, gender, gender identity or expression, or veteran status. Originally posted on Himalayas

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