HackerRank helps companies like NVIDIA, Amazon, and Microsoft hire and upskill the next generation of developers based on skills, not pedigree. Our platform is trusted by over 2,500 of the world’s most innovative companies to build strong engineering teams ready for what’s next.
Software has entered an era where humans and AI build side by side. As this shift accelerates, the definition of strong technical talent is changing. We give companies better ways to identify and invest in next-generation skills.
People at HackerRank care deeply about the impact of their work and sweat the small details so our customers can be wildly successful with products they genuinely love to use. We move with urgency and believe great outcomes come from high standards.
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.
Want to learn more about HackerRank? Check out HackerRank.com to explore our products, solutions and resources, and dive into our story and mission here.
HackerRank is a proud equal employment opportunity and affirmative action employer. We provide equal opportunity to everyone for employment based on individual performance and qualification. We never discriminate based on race, religion, national origin, gender identity or expression, sexual orientation, age, marital, veteran, or disability status. All your information will be kept confidential according to EEO guidelines.
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