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HackerRank is hiring a Data Engineer II to join its data platform team in Bangalore. The company recently modernized its data infrastructure, migrating from Redshift to StarRocks + Apache Hudi and reducing export latencies from 25 seconds to under 5 seconds. You'll work within the data team to build and maintain pipelines, support in-product data features, and contribute to datasets powering AI initiatives.
In this role, you'll build and maintain data pipelines using StarRocks (OLAP), Apache Hudi (Data Lake), Trino, and Spark under guidance from senior team members. You'll support in-product data features including exports, insights dashboards, interview analytics, and custom reports interfaces. You'll help prepare clean, structured datasets for AI-powered features like natural language querying, implement access controls and data security policies using Apache Ranger, and respond to ad-hoc data requests from internal teams (AI platform, analytics, go-to-market) by contributing to self-service pipelines. You'll write clear documentation, participate in code and design reviews, and troubleshoot data quality and pipeline issues, escalating architectural decisions to senior engineers.
You should have 2-4 years of data engineering experience with working knowledge of at least one OLAP database (StarRocks, ClickHouse, Druid, or similar). Some experience with data lake technologies (Hudi, Iceberg, or Delta Lake) is expected, though deep expertise isn't required—willingness to learn is key. Familiarity with distributed query engines (Trino/Presto) and Spark, or strong SQL/Python fundamentals with eagerness to pick these up, is important. You'll need basic understanding of data security and access control concepts, comfort in an AWS + open-source environment (or ability to ramp up quickly), and strong communication skills.
Bonus qualifications include exposure to AI/LLM-adjacent data work (RAG, vector stores, LLM pipelines), interest in how data products are consumed by non-technical end-customer-facing features, and experience at a SaaS or B2B product company. You'll thrive if you want to grow your skills on a modern, production-grade data stack, enjoy clearly-scoped problems but are eager to take on more ambiguity over time, care about reliable engineering work over setting direction, are curious about AI and want to build the pipelines that feed it, and like working closely with a senior mentor to level up quickly.
