Senior Analytics Engineer

Responsibilities

Finance data:

• accounting-system ingestion (MSSQL);

• invoices, payments, credit notes and receivables/debt;

• SaaS revenue and MRR;

• cash availability, safeguarding and FX rates;

the monthly close calendar, the monthly revenue pack and the quarterly bonus calculations.

• SaaS 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.

• B2BinPay data: transfers, volumes and commissions across legal entities; wallet balances and liquidity alerts; the daily margin report; and the commercial team's motivation scheme.

• BI 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

Requirements

Obligatory

• 4+ 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.

• Strong 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.

• Python for pipelines: REST/SOAP API ingestion, pagination, rate limits and idempotent re-runs. Airflow or a similar orchestrator.

• Dimensional (Kimball) modelling: facts and dimensions, SCD Type 2, and resolving the same customer across several source systems.

• Finance 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.

• You 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.

• English B2+ for written specs and stakeholder communication

Preferably

• Salesforce data model, SOQL and API write-backs; 1C or another ERP on MSSQL.

• Crypto payments, brokerage or fintech domain: wallets, blockchain transfers, commissions.
  dlt, the dbt semantic layer / MetricFlow, Metabase or Tableau administration and row-level security.

• Airflow on Kubernetes, Docker, GitLab CI; AWS Lambda and Step Functions.

• Building LLM or AI-assistant features over a warehouse: text-to-SQL, metric governance.

• Russian

Conditions

• Reliability: official employment from the first day, bonuses, annual employee review (salary review or bonus, feedback on work results)

• Stability: our clients are in different countries, therefore we are ready for any changes in work of any country

• Development: 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

• Active 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

• Comfort: Offices are in different countries. You can work from anywhere in the world