LILT
LILT
LILT korxonalar, davlat sektori tashkilotlari va sun’iy intellekt ishlab chiquvchilari uchun ko‘p tilli lokalizatsiya texnologiyasini yaratadigan sun’iy intellekt va SaaS kompaniyasidir. Uning platformasi 100 dan ortiq tilda xavfsiz, brend uslubiga mos tarjimalar va lokalizatsiya qilingan kontent yaratish uchun kontekstni hisobga oluvchi sun’iy intellekt modellarini mutaxassislar tomonidan amalga oshiriladigan inson tekshiruvi bilan birlashtiradi. LILT, shuningdek, maxsus modellarni o‘qitish, uzluksiz takomillashtirish, lokalizatsiya loyihalarini boshqarish, mahalliy integratsiyalar hamda korxona ichida yoki tarmoqdan uzilgan muhitlarda joylashtirishni qo‘llab-quvvatlaydi.

Data Engineering Manager at LILT (Hybrid)

Lead LILT’s data transformation and warehouse strategy for AI-powered translation. Build the Data team, establish consistent metrics, and improve infrastructure cost efficiency.

Tavsif

  • Own LILT’s data transformation layer, including dbt and the warehouse
  • Define metrics once in dbt and maintain consistency across analytics, LLM/MCP surfaces, internal dashboards, business operations, production, finance, and product
  • Operate the transformation layer and warehouse with clear pipeline ownership, testing, and cost visibility
  • Track warehouse spending and deliver measurable reductions
  • Set warehouse strategy, define ClickHouse’s role, and determine how the data layer is exposed through APIs and MCP
  • Create and lead a new Data sub-team within Platform Engineering
  • Hire, mentor, and develop a Data Engineer and a Senior Data Scientist
  • Establish the team charter and oversee delivery, quality, and on-call health
  • Define practices for using AI agents to build, test, and review pipelines and models
  • Write, review, and maintain the team’s SQL, dbt, and Python
  • Report to the Head of Platform

Talablar

  • At least seven years of experience in data or analytics engineering
  • At least two years of experience managing a small team of two to five people
  • Demonstrated success hiring and developing individual contributors
  • Fluency in SQL and Python
  • Experience building and operating production data pipelines
  • Experience with dbt or a comparable transformation layer
  • Familiarity with BigQuery, ClickHouse, Snowflake, or a similar data platform
  • Experience managing a warehouse or pipeline budget and achieving measurable cost reductions
  • Ability to turn business needs into technical plans and prioritize backlogs within headcount constraints
  • Experience owning data accountability for finance, operations, and go-to-market stakeholders
  • Understanding of B2B SaaS metrics such as ARR, ACV, gross margin, and on-time delivery
  • Regular use of AI tools, with the judgment to recognize when they help, mislead, or require verification
  • Ability to document decisions and explain tradeoffs, risks, and costs to leadership

Imtiyozlar

  • Equity
  • Opportunities for professional growth
  • Collaboration with global teams
  • Access to leading tools
  • AI-assisted hiring process with an opt-out option
  • Inclusive and transparent hiring process

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