{"id":3159625,"url":"https://alion.io/job/spotonix-staff-engineer","title":"Staff Engineer","company":{"id":1461,"name":"Spotonix","domain":"spotonix.com","url":"https://alion.io/company/spotonix","size_band":"51-200","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":null,"truth_index":null},"role":"Backend","role_family":"Backend","seniority":"staff","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":35000,"max_usd":86000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":26},"experience_years_min":9,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"C++","optional":false},{"name":"DuckDB","optional":false},{"name":"Python","optional":false},{"name":"Rust","optional":false},{"name":"Scala","optional":false},{"name":"SQL","optional":false},{"name":"dbt","optional":true},{"name":"LookML","optional":true}],"status":"live","first_seen_at":"2026-10-23T15:35:27Z","employer_posted_date":null,"last_verified_at":"2026-10-23T15:35:27Z","board_verified":false,"closed_at":null,"days_open":7,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":7},"description":"Responsibilities: \nBuild the next-generation DAX-like formula engine that turns complex evaluation contexts into efficient SQL on modern warehouses.\nOwn the core compiler and runtime for our standalone BI (parser, metadata, planning, translation, and SQL backends) and deliver a BI experience that mirrors native models while integrating tightly with Arrow- and DuckDB-based storage.\nOwn the Spotonix BI engine end to end: BI catalogue and metadata, formula-language grammar and parser, query planner and optimiser, SQL generation/execution layers, client connectivity/session management, and multi-dialect SQL support.\nDesign and optimise the query compiler that lowers expressions into an internal multidimensional algebra, applies rule- and cost-based transformations, orchestrates algebraic plans, manages evaluation contexts, and enforces lineage propagation before emitting SQL.\nEvolve the execution runtime: translate complex algebra into SQL with maximum warehouse pushdown and expose the instrumentation hooks needed by clients and regression suites.\nOwn the BI algebra itself: define and implement the suite of DAX/MDX-style operators (hierarchy navigation, cube operators, table manipulations, and iterators) and ensure each algebraic primitive ships with tests and SQL strategies.\nPartner with integrations teams to support additional warehouses, metadata loaders, and client APIs (evaluate and discover metadata) and drive observability for plan generation, SQL issuance, and cache effectiveness.\nMentor engineers on query-compilation fundamentals, context transition debugging, and deterministic developer workflows (diagram generation, regression fixtures, CLI ergonomics).\n\nRequirements: \n10-15 years building database engines, query compilers, or analytical runtimes with deep experience in SQL planning and execution internals (costing, rewrites, vectorised operators, and columnar caches).\nExpert-level Python and ease working in large metaprogrammed codebases; C++/Rust/Scala for runtime paths are a plus.\nDemonstrated ownership of multidimensional or BI algebra design, defining operators, invariants, and execution strategies across catalogues, hierarchies, and cube semantics.\nHands-on knowledge of DAX-like BI languages (MDX, LookML metrics, dbt semantic models, etc. ) and their filter/context semantics, especially CALCULATE, context transitions, and time intelligence functions.\nProven track record translating high-level DSLs into relational algebra or SQL, including dependency tracking, lineage-aware filter propagation, and multi-stage compilation pipelines.\nFamiliarity with Arrow, DuckDB, or similar columnar storage engines plus the ability to reason about concurrency, caching, and resource management in a long-running service.\nExperience building client/session infrastructure (CLI, APIs) and managing multi-dialect SQL connectors is a plus.\nComfortable operating in product-orientated environments: writing dev notes, codifying manual plans into tests, and collaborating with UI and data modelling teams.\n\nNice to Have: \nExperience ingesting PBIX or tabular models, XML/A-style protocols, or enterprise BI ecosystem tooling.\nBackground in time-intelligence modelling, date-relationship functions, or working-day calendars.\nContributions to open-source database engines, query planners, or columnar execution projects.\nPassion for developer tooling: GraphViz visualisations, SQL trace explorers, CLI experiences, and regression harnesses for semantic languages.\nSkills\nPython, SQL, compiler","description_format":"text","description_chars":3527,"description_truncated":false,"requirements":{"experience_years_min":9,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["Natural Language Processing","Knowledge Graphs","AI Data Analysts & Text-to-SQL"],"lifecycle":[{"event":"open","at":"2026-10-23T15:35:27Z"}],"visa":[],"liveness":{"score":86,"band":"hot","label":"Hiring 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