Senior Data Engineer ($40K - $50K)

🚀 What we’re building

• CodeRound AI matches top 5% tech talent to fastest growing VC funded AI startups in Silicon Valley and India.
• Candidates apply once and get UPTO 20 remote as well as onsite interview opportunities IF selected!
• Top-tier product startups in US, UK, EU, UAE & India have hired top engineers & ML folk using CodeRound

🛠️ What you’ll do

• Design, build, and scale the core data platform that powers our recommendation systems and personalization engines
• Architect clean, reliable ETL/ELT pipelines across GitHub, StackOverflow, Reddit, job feeds, and internal systems
• Build and maintain real-time data workflows that support matching, scoring, and analytics
• Collaborate closely with ML engineers to design data adapters, feature pipelines, and interfaces for model training + serving
• Own data modeling for onboarding flows, engagement metrics, dashboards, and operational analytics
• Ensure high-quality, observable, fault-tolerant data systems
• Set standards for data quality, governance, and best practices across the company

🚀 Why join us now?

• Ownership — You’ll own large chunks of product and backend.
• Velocity — We ship fast. No red tape. Just real work and real impact.
• Customers love us — We’re not guessing. We’re scaling.
• Learning — Work with founders who’ve built and exited companies, and learn the ropes of building a startup from scratch.
• Growth — If you're good, you’ll grow fast here — in role, scope, and compensation.

🙌 You might be a great fit if you:

• Have

  3–6 years

  of experience in Data Engineering
• Know

  Python/Go/Scala

  , strong SQL, and modern data tooling
• Have experience with

  Airflow, DBT, Spark, Kafka, Flink

  , or similar
• Have built scalable pipelines, streaming systems, or data warehouses
• Understand how ML teams consume and depend on data
• Think in systems and care deeply about clean, maintainable architecture
• Thrive in zero-to-one environments, ambiguity, and fast-paced execution

⚡ Bonus points if you:

• Have built data interfaces for ML model training & real-time serving
• Bring a strong understanding of distributed systems
• Have shipped side projects, open-source contributions, or infra tools