About the role

HackerRank's data platform has just come through a major modernisation - moving from Redshift to StarRocks + Apache Hudi, and cutting export latencies from 25 seconds to under 5. The foundation is in place, and we're now building toward an AI-native data layer that will power features like natural language querying for HackerRank for Work customers.

As a Data Engineer II, you'll work within the data team to build and maintain pipelines, support in-product data features, and contribute to the datasets that power our AI initiatives. You'll work closely with senior engineers and the Lead Data Engineer, picking up well-scoped problems and growing into broader ownership over time.

What you will do

• Build and maintain data pipelines on our stack - StarRocks (OLAP), Apache Hudi (Data Lake), Trino, and Spark - under guidance from senior team members.
• Support in-product data features such as exports, insights dashboards, interview analytics, and the Custom Reports interface.
• Help prepare clean, structured datasets that feed into AI-powered features like natural language querying.
• Implement access controls and data security policies (e.g., Apache Ranger) as defined by senior engineers.
• Respond to and help reduce ad-hoc data requests from internal teams (AI platform, analytics, go-to-market) by contributing to self-service pipelines.
• Write clear documentation and participate in code/design reviews.
• Troubleshoot data quality and pipeline issues, escalating architectural decisions to senior engineers.

Who you are

• 2-4 years of data engineering experience.
• Working knowledge of at least one OLAP database (StarRocks, ClickHouse, Druid, or similar).
• Some experience with data lake technologies (Hudi, Iceberg, or Delta Lake) - deep expertise not required, willingness to learn is.
• Familiarity with distributed query engines (Trino/Presto) and Spark, or strong SQL/Python fundamentals with eagerness to pick these up.
• Basic understanding of data security and access control concepts.
• Comfortable in an AWS + open-source environment, or quick to ramp up.
• Good communicator who can explain their work to teammates and ask for help when scoping is unclear.

Even better if you have

• Any exposure to AI/LLM-adjacent data work - even coursework or side projects with RAG, vector stores, or LLM pipelines.
• Interest in how data products get consumed by non-technical, end-customer-facing features.
• Experience at a SaaS or B2B product company.

You will thrive in this role if

• You want to grow your skills on a modern, production-grade data stack.
• You like clearly-scoped problems but are eager to take on more ambiguity over time.
• You care about doing good, reliable engineering work more than being the one setting direction.
• You're curious about AI and want to build the pipelines that feed it, even if you're not designing the AI systems yourself.
• You like working closely with a senior mentor and leveling up quickly.