{"id":2498582,"url":"https://alion.io/job/lusha-senior-data-platform-engineer","title":"Senior data platform engineer","company":{"id":49222,"name":"Lusha","domain":"lusha.com","url":"https://alion.io/company/lusha","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Comeet","truth_index":null},"role":"Data Science","role_family":"Data Science","seniority":"senior","employment_type":"full_time","work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Tel Aviv, Israel"],"countries":["IL"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":76000,"max_usd":194000,"period":"year","method":"global_role_cell_scaled_by_country","sample_n":2324},"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Amazon S3","optional":false},{"name":"Apache Kafka","optional":false},{"name":"AWS","optional":false},{"name":"CI/CD","optional":false},{"name":"Databricks","optional":false},{"name":"Delta Lake","optional":false},{"name":"Docker","optional":false},{"name":"ElasticSearch","optional":false},{"name":"Embeddings","optional":false},{"name":"IAM","optional":false},{"name":"Kubernetes","optional":false},{"name":"LLM","optional":false},{"name":"Model Context Protocol","optional":false},{"name":"Python","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false},{"name":"Terraform","optional":false},{"name":"FinOps","optional":true}],"status":"live","first_seen_at":"2026-10-11T16:53:19Z","employer_posted_date":"2026-10-11","last_verified_at":"2026-10-17T21:29:09Z","board_verified":true,"closed_at":null,"days_open":6,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":6},"description":"Description\nAt Lusha, we're building for builders. We build fast and AI-first, so we look for builders. By a builder, we mean someone who turns \"maybe\" into \"done\".\nWe're looking for a Senior Data Platform Engineer to join the Data Platform team, which owns the infrastructure every data team at Lusha runs on and sits between DevOps and the Data groups. You'll be the Databricks admin (Unity Catalog, compute, governance, cost), the Confluent (Kafka) and CDC admin, and own Airflow, Elasticsearch, the databases, the data S3 estate, and the Kubernetes cluster underneath. Your job is to make the platform fast, cheap, governed, and boring: if it's broken, you fix it, if it's manual, you automate it.\nHands-on experience using AI coding tools daily, and building or integrating LLM and agent tooling into real workflows, is a must for this role.\nThis role is based in Tel Aviv. We work in a hybrid model, with 3 days a week in the office.\nThis might be for you if:\nYou enjoy designing, building, and running large scale batch and streaming data pipelines in production, and owning what you ship, including when it breaks\nYou like administering and evolving core platforms: Databricks, Confluent Kafka and CDC pipelines, Airflow, and Elasticsearch\nYou care about reliability, performance, and cost of a shared data platform used across R&D\nYou enjoy setting the engineering standard for data work: testing, observability, cost tagging, documentation\nYou like driving architecture decisions across Databricks, Kafka, Elasticsearch, and AWS\nYou actively use AI tools and build self-service tooling, including MCP servers and agent interfaces, so teams can operate the platform safely\nRequirements\n5+ years hands-on building and operating large scale data pipelines, batch and streaming, in production\nDeep Spark and Databricks experience: Delta Lake, Unity Catalog, job and cluster tuning, Structured Streaming or DLT\nStreaming and CDC experience: Kafka (Confluent a plus), Debezium or equivalent, schema evolution and its failure modes\nExperience writing Airflow DAGs and operating the platform itself\nExpert Python and SQL, clean, tested, performant\nStrong data modeling and architecture judgment, with the ability to explain tradeoffs in scale, performance, and cost\nInfra literacy: comfortable with AWS (S3, IAM, networking basics), Terraform, Docker and Kubernetes, and CI/CD\nProven experience leading cross-team technical initiatives end to end, from ambiguous ask to shipped and adopted\nProven experience using AI coding tools daily, with LLM and agent tooling (MCP, embeddings, vector search) built into real workflows\nNice to have:\nElasticsearch at scale: indexing pipelines, cluster operations, reindex and rollout strategies\nFinOps or cloud cost management for data platforms\nVault or similar secrets management, and Kubernetes operations beyond 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