Data Engineer

Company Description Bloom AI builds applied intelligence solutions that help decision-makers turn dispersed data into clear, actionable signals. The company partners with asset managers, insurers, private equity firms, and enterprise teams to bridge modern data infrastructure and real business action. By combining curated domain data, structured intelligence models, and generative AI, Bloom AI delivers continuous, contextual, decision-ready insights rather than static dashboards. Its intelligence layers span competitor, market, distribution, and marketing, embedding signals directly into workflows. Bloom AI operates from the U.S. and India, working globally with clients who value better judgment over simply more data.
Role Description This is a full-time, hybrid Data Engineer role based in New Delhi, with flexibility for partial work-from-home arrangements. The Data Engineer will design, build, and maintain scalable data pipelines that power Bloom AI's intelligence layers and products. Responsibilities include developing and optimizing ETL processes, modeling data for analytics and AI workloads, and implementing data warehousing solutions that ensure high data quality, reliability, and performance. The role will involve collaborating closely with data scientists, product teams, and domain experts to understand requirements and translate them into robust data infrastructure. The Data Engineer will also monitor and troubleshoot data workflows, improve automation, and contribute to best practices in security, observability, and documentation.
Qualifications

• Candidates should possess strong Data Engineering skills, including building and maintaining data pipelines and working with modern data stack tools.
• Candidates should possess solid Data Modeling skills to design efficient schemas and structures for analytics and AI use cases.
• Candidates should possess experience with Extract Transform Load (ETL) processes, including orchestration, optimization, and error handling.
• Candidates should possess Data Warehousing skills, including working with cloud data warehouses and implementing scalable storage solutions.
• Candidates should possess Data Analytics skills to interpret data, support decision-making, and collaborate with analytics and AI teams.
• Relevant experience with SQL and one or more programming languages (such as Python or Java) for data processing and automation.
• Familiarity with cloud platforms (e.g., AWS, GCP, or Azure), data pipeline orchestration tools, and version control systems.
• Bachelor's or Master's degree in Computer Science, Engineering, Information Systems, or a related field, or equivalent practical experience.
• Ability to work effectively in a hybrid environment, communicate clearly with cross-functional teams, and manage multiple priorities.