Senior Data Platform Engineer

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. This is a hands-on engineering role where you will write code every week to 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).

- 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.

- 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.

- Experience on AWS or GCP.

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.