Lead Data Engineer

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.

About the role

HackerRank's data platform is at an inflection point. We've completed a multi-year modernisation - migrating from Redshift to StarRocks + Apache Hudi - and cut export latencies from 25 seconds to under 5 seconds. The infrastructure groundwork is done. Now we're building the AI-native data layer that will power revenue-generating features like natural language querying for HackerRank for Work customers.

As Lead Data Engineer, you'll be a senior individual contributor at the heart of the data organisation - owning complex platform decisions, collaborating cross-functionally with AI, product, and go-to-market teams, and shipping data-driven features that directly drive revenue. This is a greenfield opportunity to shape the next phase of data at HackerRank.

What you will do

• Own and evolve the data platform - StarRocks (OLAP), Apache Hudi (Data Lake), Trino, Spark, and Apache Ranger - ensuring performance, reliability, and security at scale.
• Build the next-gen AI-optimised data layer: clean, structured datasets that power natural language querying and AI add-on features for HackerRank for Work customers.
• Own in-product data features - exports, insights dashboards, interview analytics, and the self-serve Custom Reports interface.
• Enable self-service pipelines for internal teams (AI platform, analytics, go-to-market), reducing ad-hoc data requests and scaling data access across the org.
• Enforce robust data security - access controls, Apache Ranger policies, and confidence-scoring guardrails for AI-generated outputs.
• Lead technical design reviews and define engineering standards for the data team.
• Partner with PMs and business stakeholders to proactively identify and scope AI-enabled data use cases.

Who you are

• 6+ years of data engineering experience, with at least 2 years in a senior or lead capacity.
• Deep hands-on expertise with OLAP databases - StarRocks, ClickHouse, Druid, or similar.
• Strong experience with data lake technologies - Apache Hudi, Iceberg, or Delta Lake.
• Proficient with distributed query engines (Trino / Presto) and batch/streaming compute with Apache Spark.
• Solid understanding of data security, RBAC, and access control tools like Apache Ranger.
• Comfortable working in a hybrid AWS + open-source self-managed environment.
• Strong communicator who can translate technical decisions for non-technical stakeholders and drive cross-functional projects independently.

Even better if you have

• Hands-on experience with AI/LLM-adjacent data work - confidence scoring, agentic pipelines, RAG architectures, or vector stores.
• Prior exposure to agentic workflows and understanding how to operationalise emerging AI concepts at production scale.
• Experience scaling data infrastructure at a SaaS or B2B product company.
• Familiarity with natural language querying interfaces or building data products for end-customer consumption.

You will thrive in this role if

• You're energised by working on a platform that's both technically mature and still has enormous greenfield ahead of it.
• You don't wait for a PM to hand you a roadmap - you proactively connect data capabilities to business outcomes.
• You care as much about how other teams use data as you do about the pipelines that produce it.
• You're genuinely curious about AI and want to be close to where data and intelligence intersect.
• You thrive in lean, cross-functional environments where your decisions have visible, company-wide impact.

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