{"id":3522100,"url":"https://alion.io/job/netcore-cloud-senior-data-platform-engineer","title":"Senior Data Platform Engineer","company":{"id":59452,"name":"Netcore Cloud","domain":"netcore.ai","url":"https://alion.io/company/netcore-cloud","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":null,"truth_index":null},"role":"Data Science","role_family":"Data Science","seniority":"senior","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Bengaluru, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":22000,"max_usd":48000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":75},"experience_years_min":4,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Apache Hudi","optional":false},{"name":"Apache Iceberg","optional":false},{"name":"Go","optional":false},{"name":"Java","optional":false},{"name":"Python","optional":false},{"name":"Rust","optional":false},{"name":"Aerospike","optional":true},{"name":"Apache Kafka","optional":true},{"name":"AWS","optional":true},{"name":"Cassandra","optional":true},{"name":"ClickHouse","optional":true},{"name":"Delta Lake","optional":true},{"name":"Dimensional Modeling","optional":true},{"name":"Druid","optional":true},{"name":"Flink","optional":true},{"name":"GCP","optional":true},{"name":"Google BigQuery","optional":true},{"name":"Snowflake","optional":true},{"name":"Spark","optional":true},{"name":"SQL","optional":true}],"status":"live","first_seen_at":"2026-10-30T11:51:17Z","employer_posted_date":null,"last_verified_at":"2026-10-30T11:51:17Z","board_verified":false,"closed_at":null,"days_open":0,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":0},"description":"Role : Senior Data Platform Engineer R&D.\n\nAbout Us : \n\nNetcore.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.\n\nRole Summary : \n\nYou 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.\n\nWhat You'll Do : \n\n- Design and run rigorous benchmarks and scalability studies across databases, storage engines, messaging and streaming systems.\n\n- Prototype and stress-test new architectures for high-throughput data ingestion, real-time analytics and large-scale personalization workloads.\n\n- Evaluate open table formats and lakehouse stacks (Iceberg, Hudi, Delta) and their catalogs, query engines and storage layers.\n\n- Compare technology options and give build-versus-buy recommendations backed by experimental data.\n\n- Write design documents, RFCs, benchmark reports and engineering articles that inform technology decisions.\n\n- Move successful prototypes into production-ready solutions together with platform and product engineering teams.\n\n- Track emerging data infrastructure technologies and share actionable insights with engineering leadership.\n\nMust-Have Skills : \n\n- Strong programming in Java and Python (Go or Rust is a plus) for rapid prototyping.\n\n- Hands-on experience building data pipelines and data platforms at scale, using Kafka and Spark (or Flink).\n\n- Working knowledge of at least one open table format (Iceberg, Hudi or Delta Lake) and how it differs from plain files on object storage.\n\n- Experience with two or more NoSQL or analytical databases (e.g., Cassandra, MongoDB, ClickHouse, Druid, Aerospike, BigQuery, Snowflake).\n\n- Strong data modeling skills : normalized vs. denormalized design, dimensional modeling, query-driven NoSQL design, partitioning and key design, and schema evolution.\n\n- Strong SQL and query optimization : reading and tuning execution plans, indexing and partitioning strategies, join and aggregation optimization.\n\n- Solid understanding of columnar and row file formats (Parquet, Avro, ORC), including compression, predicate pushdown and schema evolution.\n\n- Strong data structures, algorithms and distributed systems fundamentals.\n\n- Experience benchmarking and profiling workloads to classify them as CPU-bound, memory-bound or I/O-bound.\n\n- Experience on AWS or GCP.\n\nQualifications : \n\n- Bachelor's or Master's degree in Computer Science, Engineering or a related field.\n\n- 4 - 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