Role: Senior Data Platform Engineer - R&D;

About Us

Netcore.ai is a leading AI-powered B2B SaaS Customer Experience and Marketing Technology platform, helping 6,500+ brands across 20+ countries deliver personalized customer experiences at scale. Our engineering teams build highly scalable, cloud-native products that process billions of customer interactions every day.

Role Summary

You will evaluate, benchmark and prototype next-generation data platform technologies (open table formats, streaming systems, NoSQL and OLAP databases) for Netcore’s high-scale omnichannel marketing platform. You will run experiments, build proof-of-concept systems, and turn the results into clear recommendations that engineering and product teams use to decide what we adopt, build or buy.

This is a hands-on engineering role. You will write code every week, and your findings will shape our platform direction.

What You'll Do

- Design and run rigorous benchmarks and scalability studies across databases, storage engines, messaging and streaming systems
- Prototype and stress-test new architectures for high-throughput data ingestion, real-time analytics and large-scale personalization workloads
- Evaluate open table formats and lakehouse stacks (Iceberg, Hudi, Delta) and their catalogs, query engines and storage layers
- Compare technology options and give build-versus-buy recommendations backed by experimental data
- Write design documents, RFCs, benchmark reports and engineering articles that inform technology decisions
- Move successful prototypes into production-ready solutions together with platform and product engineering teams
- Track emerging data infrastructure technologies and share actionable insights with engineering leadership

Must-Have Skills

- Strong programming in Java and Python (Go or Rust is a plus) for rapid prototyping.
- Hands-on experience building data pipelines and data platforms at scale, using Kafka and Spark (or Flink).




- Working knowledge of at least one open table format (Iceberg, Hudi or Delta Lake) and how it differs from plain files on object storage.
- Experience with two or more NoSQL or analytical databases (e.g., Cassandra, MongoDB, ClickHouse, Druid, Aerospike, BigQuery, Snowflake), including the trade-offs between them.
- Strong data modeling skills: normalized vs. denormalized design, dimensional modeling, query-driven NoSQL design, partitioning and key design, and schema evolution.
- Strong SQL and query optimization: reading and tuning execution plans, indexing and partitioning strategies, join and aggregation optimization, and diagnosing slow queries on both relational and analytical engines.
- Solid understanding of columnar and row file formats (Parquet, Avro, ORC), including compression, predicate pushdown and schema evolution.
- Strong data structures, algorithms and distributed systems fundamentals.
- Experience benchmarking and profiling workloads to classify them as CPU-bound, memory-bound or I/O-bound, using tools such as perf, top/htop, vmstat, iostat, strace or flame graphs, and designing controlled experiments to interpret results.
- Experience on AWS or GCP.

Nice to Have

- Benchmarking tools such as YCSB, Sysbench or HammerDB, and cloud-native observability stacks
- Trino, Flink, Databricks, Polaris/Nessie or Alluxio
- Vector databases (e.g., Milvus, Pinecone, pgvector) and graph databases (Neo4j, TigerGraph)
- Probabilistic data structures and compressed bitmaps (Apache DataSketches, Roaring Bitmaps)
- Open-source contributions, conference talks,



published technical papers or engineering blog posts
- Experience taking experimental prototypes into production

Qualifications

- Bachelor’s or Master’s degree in Computer Science, Engineering or a related field
- 4–10 years of experience in backend, data platform with demonstrated experience developing, evaluating or benchmarking large-scale systems

Impact Metrics

- Number of successful experimental prototypes incubated and adopted by engineering teams.
- Published benchmarks, whitepapers, or technical reports that inform strategic technology decisions.
- Measurable improvements in platform scalability, reliability, or engagement attributed to research findings and new tech integrations.

Why Join Us?

- Build products used by 6,500+ global brands.
- Solve engineering challenges at scale using modern technologies.
- Work with cloud-native architectures, distributed systems, AI-powered development tools, and a high-performing engineering team.
- Thrive in a culture of ownership, innovation, and continuous learning.

Global Recognitions

- Leader in Commerce Search and Product Discovery in The Forrester Wave 2023
- The only Forrester-rated global vendor in Product Discovery, Cross Channel Marketing Hubs and Email.
- Leader in Marketing Platforms in G2’s Winter 2024 Grid
- Top 20 global Google Cloud Partner
- Appraised at Level 3 of ISACA’s CMMI® by Equalitas Certifications Limited
- Great Place to Work® for six consecutive years in India

Know More About Us

- Agentic Marketing Platform: Co-Marketer
- Our Growth Story: The Proficorn Playbook – How Netcore Built a $100M+ ARR Business Without VC Funding
- Life at Netcore: Explore our culture, and employee experiences
- Blogs
- Customer Success Stories
- Product & Tech Documentation
- Be a Proficorn: Watch/listen to our podcast of Netcore’s leaders in conversation with industry experts

~ Netcore is an equal prospect employer.

📌 Senior Data Platform Engineer (Bengaluru)
🏢 Netcore
📍 Bengaluru