{"id":4210893,"url":"https://alion.io/job/b2broker-senior-analytics-engineer","title":"Senior Analytics Engineer","company":{"id":56895,"name":"B2BROKER","domain":"b2broker.com","url":"https://alion.io/company/b2broker","size_band":"201-500","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Huntflow","truth_index":null},"role":"Analytics","role_family":"Analytics","seniority":"senior","employment_type":null,"work_mode":"remote","remote_scope":"worldwide","remote_scope_basis":"posting_text","remote_working_hours":null,"hiring_geo_confidence":"inferred","locations":["Dubai, United Arab Emirates"],"countries":["AE"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":4,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"1C","optional":false},{"name":"AWS","optional":false},{"name":"AWS Lambda","optional":false},{"name":"AWS Step Functions","optional":false},{"name":"dbt","optional":false},{"name":"Dimensional Modeling","optional":false},{"name":"Docker","optional":false},{"name":"GitLab CI","optional":false},{"name":"Google Sheets","optional":false},{"name":"Kubernetes","optional":false},{"name":"LLM","optional":false},{"name":"Metabase","optional":false},{"name":"MS SQL","optional":false},{"name":"PostgreSQL","optional":false},{"name":"Python","optional":false},{"name":"Rest API","optional":false},{"name":"Slack","optional":false},{"name":"SOAP","optional":false},{"name":"SQL","optional":false},{"name":"Tableau","optional":false}],"status":"live","first_seen_at":"2026-11-13T00:58:44Z","employer_posted_date":"2026-11-13","last_verified_at":"2026-11-13T00:58:44Z","board_verified":true,"closed_at":null,"days_open":0,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":0},"description":"Responsibilities\nFinance data:\naccounting-system ingestion (MSSQL);\ninvoices, payments, credit notes and receivables/debt;\nSaaS revenue and MRR;\ncash availability, safeguarding and FX rates;\nthe monthly close calendar, the monthly revenue pack and the quarterly bonus calculations.\nSaaS and sales data: Salesforce ingestion and write-back of computed fields, sales pipeline and activity marts, product usage and revenue for our SaaS lines, and marketing attribution.\nB2BinPay data: transfers, volumes and commissions across legal entities; wallet balances and liquidity alerts; the daily margin report; and the commercial team's motivation scheme.\nBI and reporting: Metabase and Tableau dashboards, including row-level security; Slack reports and Google Sheets integrations; the certified metrics that our AI assistant is allowed to use\nRequirements\nObligatory\n4+ years in analytics engineering or data engineering. At least 2 of those years with dbt in production: incremental models, snapshots, seeds, tests with severity, and macros.\nStrong PostgreSQL. That includes window functions, deterministic dedup and reading query plans. It also includes making schema changes on a shared warehouse without breaking other teams.\nPython for pipelines: REST/SOAP API ingestion, pagination, rate limits and idempotent re-runs. Airflow or a similar orchestrator.\nDimensional (Kimball) modelling: facts and dimensions, SCD Type 2, and resolving the same customer across several source systems.\nFinance fluency. You can explain: AR ageing; MRR movements (new, expansion, churn); revenue vs. cash timing; FX conversion; intercompany elimination. You can also reconcile a mart against the accounting export to the cent.\nYou work directly with business owners: Finance, Treasury, Sales and product teams. You turn a vague request into a written spec and push back when the definition is unclear. You own the number after it ships.\nEnglish B2+ for written specs and stakeholder communication\nPreferably\nSalesforce data model, SOQL and API write-backs; 1C or another ERP on MSSQL.\nCrypto payments, brokerage or fintech domain: wallets, blockchain transfers, commissions.dlt, the dbt semantic layer / MetricFlow, Metabase or Tableau administration and row-level security.\n\nAirflow on Kubernetes, Docker, GitLab CI; AWS Lambda and Step Functions.\nBuilding LLM or AI-assistant features over a warehouse: text-to-SQL, metric governance.\nRussian\nConditions\nReliability: official employment from the first day, bonuses, annual employee review (salary review or bonus, feedback on work results)\nStability: our clients are in different countries, therefore we are ready for any changes in work of any country\nDevelopment: a lot of projects and products, which means increasing expertise in working with different technologies, or even switching to completely new ones for you within the company\nActive corporate life: we participate in thematic conferences and forums in our cool sphere of business, corporate parties in the best restaurants of the city with participation of stars, etc\nComfort: Offices are in different countries. 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