• Architect complex, high-volume data pipelines for production use. • Design and implement scalable data models serving multiple product and internal teams. • Own data quality frameworks and standards across key data products. • Build reusable patterns for transformations and metrics to drive efficiency. • Define and maintain core business metrics and Key Performance Indicators (KPIs) in partnership with Analytics. • Own the data products used across the company, ensuring reliability and performance. • Set and promote standards for data modeling and pipeline development. • Partner closely with Analytics, Data Science, and Machine Learning teams on requirements to reduce friction and accelerate their work. • Mentor engineers and actively participate in the hiring process.

• Design, develop, and maintain scalable data pipelines and analytics solutions in GCP. • Develop solutions for collecting, processing, and analyzing LLM token usage data. • Build forecasting and anomaly detection mechanisms to monitor AI consumption patterns. • Optimize and maintain BigQuery datasets and cloud-based processing environments. • Collaborate with cross-functional teams to translate business needs into scalable AI/data solutions. • Ensure high-quality data processing through testing, monitoring, and automation best practices. • Contribute to data architecture, analytics frameworks, and continuous improvement initiatives.

Role Description Corvi Technologies is building an AI-powered job matching platform for OPT, H-1B, and international job seekers in the USA — and we're currently developing a Chrome Extension that automates job discovery across top career portals. As a Data & Product Research Intern, you'll be a core part of this build. You'll navigate real-world job sites, validate how our extension behaves, and help us turn raw data into clean, structured insights. This is hands-on, meaningful work — not coffee runs or formatting decks. - Visit designated careers portals (Apple, Google, Microsoft, Amazon, and 20+ others) and systematically browse and interact with job listings as per a daily checklist. - Test Corvi's Chrome Extension in real-time — click through job listings, trigger extension actions, and observe how it captures and processes job data. - Log findings in structured Google Sheets — job title, location, posting date, URL, category, and any anomalies observed. - Report bugs, UI issues, or unexpected extension behaviour with clear steps to reproduce — no coding required, just clear observation. - Organize and clean collected job data: remove duplicates, standardize formats, and flag inconsistencies. - Compile brief weekly summaries of data patterns — which portals have the most OPT-friendly listings, trending roles, location clusters, etc. - Suggest improvements to the data collection checklist and testing workflows based on what you encounter daily. Qualifications - Currently pursuing a Bachelor's degree (3rd year preferred) in any stream — Engineering, BBA, BCA, B.Com, Statistics, or related fields are all welcome. - Detail-oriented and methodical — you notice when something looks off and you document it clearly. - Comfortable spending focused time browsing multiple websites and logging data systematically. - Basic familiarity with Google Sheets or Excel — if you know VLOOKUP or basic filters, you're ahead of the curve. - Reliable internet connection and a laptop with Chrome browser installed. - Good written English — your bug reports and data notes need to be clear and concise. - Curiosity about how tech products are built and how data powers decisions. Benefits - Work on a live product used by real users — not a mock project or case study. - Get a performance-based Letter of Recommendation from the founding team. - Flexible 4-hour schedule — fits perfectly around your college timetable. - Top performers may be offered a pre-placement or extended role post-graduation. - Direct exposure to a US-market SaaS startup — a strong resume differentiator.

• Apply knowledge of health care and database management to analyze clinical data, and to identify and report trends. • Design and build modern data-centric software applications to support clinical and operational processes across all parts of the healthcare system. • Work closely with the Product, Platform, and Architecture teams to deliver on joint efforts. • Build data pipelines and transformations, data enrichment processes, provisioning layers, and user interfaces to meet the requirements of key initiatives. • Mentor and assist less experienced Data Engineers and participate in research and development of new technologies to help set up repeatable processes or templates for other Data Engineers to follow.