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About The Role Build the next-generation DAX-like formula engine that turns complex evaluation contexts into efficient SQL on modern data warehouses. As a Staff Engineer on the BI Engine team, you will own the core compiler and runtime for our standalone dax_engine spanning the parser, metadata layer, query planner, SQL translation backends, and client connectivity and deliver a BI experience that faithfully mirrors native models while integrating tightly with Arrow- and DuckDB-based storage. Responsibilities Engine Ownership: Own the Spotonix BI engine end to end BI catalog and metadata, formula-language grammar and parser, query planner and optimizer, SQL generation,execution layers, client connectivity,session management, and multi-dialect SQL support.Drive observability for plan generation, SQL issuance, and cache effectiveness, partnering with integrations teams to support additional warehouses, metadata loaders, and client APIs. Compiler & Query Planning Design and optimize 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.Evolve the execution runtime translate complex algebra into SQL with maximum warehouse pushdown and expose the instrumentation hooks needed by clients and regression suites. BI Algebra Design Own the BI algebra itself define and implement the suite of DAX,MDX-style operators (hierarchy navigation, cube operators, table manipulations, iterators) and ensure each algebraic primitive ships with tests and SQL strategies.Expand DAX function coverage and time-intelligence patterns while maintaining correctness and semantic fidelity across all supported warehouse backends. Technical Leadership & Collaboration Mentor engineers on query-compilation fundamentals, context transition debugging, and deterministic developer workflows (diagram generation, regression fixtures, CLI ergonomics).Collaborate with UI and data-modeling teams, writing dev notes and codifying manual plans into robust, repeatable test fixtures. Qualifications Required 1015 years building database engines, query compilers, or analytical runtimes with deep experience in SQL planning and execution internals (costing, rewrites, vectorized operators, columnar caches).Expert-level Python and ease working in large metaprogrammed codebases; C++, Rust, or Scala for runtime paths is a plus.Demonstrated ownership of multidimensional or BI algebra design defining operators, invariants, and execution strategies across catalogs, hierarchies, and cube semantics.Hands-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.Proven track record translating high-level DSLs into relational algebra or SQL, including dependency tracking, lineage-aware filter propagation, and multi-stage compilation pipelines.Familiarity with Arrow, DuckDB, or similar columnar storage engines, plus the ability to reason about concurrency, caching, and resource management in a long-running service. Preferred Experience building client,session infrastructure (CLI, APIs) and managing multi-dialect SQL connectors.Comfortable operating in product-oriented environments writing dev notes, codifying manual plans into tests, and collaborating with UI and data-modeling teams. Nice to Have Experience ingesting PBIX or Tabular models, XML,A-style protocols, or enterprise BI ecosystem tooling.Background in time-intelligence modeling, date relationship functions, or working-days calendars.Contributions to open-source database engines, query planners, or columnar execution projects.Passion for developer tooling GraphViz visualizations, SQL trace explorers, CLI experiences, and regression harnesses for semantic languages. What Success Looks Like You deliver a DAX-like engine that faithfully reproduces complex evaluation semantics context transitions, lineage-aware filters, manual rowset DAGs while compiling to warehouse-native SQL that hits performance SLAs. Query authors and integration teams gain a predictable evaluate() surface, cache hit rates climb, SQL traces look hand-written, and the coverage of DAX functions plus time-intelligence patterns keeps expanding without sacrificing correctness. Spotonix is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. .
Here's how to pick the right one and stand out in your application.
144.883Jobs
31.687IN
81%EN
That number is real. WorkMundi's database shows 144,883 open engineer roles across the world. India has the most with 31,687 jobs, followed by the United States with 30,084. If you just finished reading one job ad and felt paralyzed by choice, you're not alone—but this scale is actually an advantage. It means you can afford to be selective.
Start by geography and language. The majority of engineer ads—117,837 of them—have the job posting text written in English. Use that as one filter, but remember: the ad text language tells you nothing about whether the role actually requires you to speak English day-to-day. Read the job description carefully. Then check which countries have the volume you're targeting. Singapore, Poland, and Australia round out the top five after India and the US.
Next, learn who's hiring. Accenture has posted 2,801 engineer roles. andurilindustries, speechify, and jobgether are also actively recruiting. If you're applying to one of these names, research their hiring patterns and interview style before you apply. That homework pays off.
When you interview, expect the question every engineer hears: 'Tell me about a time you had to debug a problem that wasn't in your job description.' Have a specific story ready—not a general one. Name the tools, the deadline pressure, and what you learned. Hiring managers listen for whether you see problem-solving as part of the role itself, not a favour.