Sr. Software Engineer - Data

About the Role

At 6sense, data powers our AIfirst products at massive scale. We're looking for a Senior Software Engineer - Data who can design, own, and evolve largescale data systems endtoend, while using AI tools (prompting + vibe coding) as a force multiplier.

This is not an ML research role. AI here means leveraging LLMs to accelerate engineering velocity and improve system quality. At this level, you are expected to drive architecture, lead complex problem solving, and influence technical direction across systems.

What You'll Do

End-to-End System Ownership

• Design, build, and operate large-scale batch and real-time data pipelines.
• Take ownership of entire data domains (not just pipelines) including ingestion transformation serving layers.
• Ensure high reliability, observability, and maintainability of data systems.

System Design & Architecture

• Architect scalable, fault-tolerant data platforms handling high-throughput workloads.
• Make critical decisions on data modeling, storage formats, and compute frameworks.
• Design systems with cost efficiency, performance, and data freshness trade-offs in mind.

Technical Leadership

• Lead design discussions and review complex system architectures.
• Mentor IC3 engineers; raise engineering bar across code quality, testing, and design.
• Proactively identify and drive platform-level improvements and simplifications.

Advanced Data Engineering

• Develop and optimize high-performance SQL and distributed computations at scale.
• Work deeply with Spark, Kafka, Hive, Presto, or equivalent ecosystems.
• Solve data consistency, deduplication, and large-scale data quality challenges.

AI-Enabled Engineering (Required)

• Use AI tools (Copilot, ChatGPT, Cursor, etc.) for:
• Accelerating development, debugging, and refactoring
• Generating and optimizing SQL and pipelines
• Understanding large codebases and diagnosing production issues
• Demonstrate advanced prompting strategies and ability to operationalize AI safely.
• Balance speed vs correctness-validate performance, security, and correctness rigorously.

Cross-Team Impact

• Partner with Data Science, Platform, and Backend teams to build datasets powering products.
• Influence roadmap decisions through technical insights and trade-offs.
• Contribute to data platform standards, reusable frameworks, and best practices.

What We're Looking For :

Experience

• 6-10 years of experience in data engineering or distributed systems

Core Skills

• Strong coding expertise in Python and/or Java
• Deep expertise in SQL optimization on large-scale datasets
• Hands-on experience with big data technologies (Spark, Kafka, Hive, Presto)
• Experience building systems on AWS (S3, EMR, Redshift, EC2)

Advanced Capabilities

• Proven ability to design and scale distributed systems independently
• Strong understanding of:
• Data modeling and schema evolution
• Streaming vs batch trade-offs
• Data SLAs and cost optimization
• Experience handling production-grade failures and large-scale debugging

AI Productivity

• Practical, real-world use of AI tools to improve engineering velocity
• Ability to use AI strategically, not just tactically

Nice to Have

• Experience with NoSQL / MPP systems
• Exposure to Docker / Kubernetes
• Experience building or supporting AI/LLM-powered systems or data pipelines

One-Line Summary on Skills

• Python + SQL + Distributed Systems (Spark/Kafka) + AWS + System Design + AI-enabled Development