Data Analytics Engineer (Maternity Cover)

About the role

Datarails is the AI operating system for finance teams, uniting financial and operational data through its FinanceOS data layer. It is looking for a Data Analytics Engineer with strong technical skills to join the Marketing Data team in Tel Aviv. The candidate will define metrics, build the analysis behind them and keep the underlying data reliable, reporting to the VP Growth and working directly with Marketing, Product and Sales leaders. The marketing data model on BigQuery is already in production.

Key responsibilities

• Work with revenue leaders to turn business questions into metric definitions, KPIs and measurement plans.
• Build analysis and dashboards on acquisition, conversion, activation, feature adoption and retention.
• Identify gaps in tracking and work with R&D to close them.
• Maintain and extend existing pipelines and models (Airflow, Fivetran, ad platform connectors, BigQuery transformations).
• Monitor data quality and fix issues before they reach stakeholders.
• Document metric definitions, models and decisions as you go.

Required profile

• 3+ years as an analytics engineer or data analyst, preferably in B2B SaaS.
• Experience defining metrics and KPIs with business stakeholders and building the dashboards that track them.
• Experience working across business domains (marketing, sales, product, finance) and learning a new team's data quickly.
• Ability to work independently, taking a loosely defined question and delivering it without close technical supervision.

Required skills

• Proficiency in SQL and Python for data processing, analysis and automation.
• Data modeling and warehousing in a cloud data warehouse, ideally BigQuery on GCP.
• ETL/ELT pipelines from multiple sources orchestrated with Apache Airflow.
• Data observability: pipeline health, freshness and quality.
• Git, version control, CI/CD, Docker and Terraform.
• Nice to have: marketing analytics (attribution, funnel, campaign performance), Fivetran, Funnel.io or dbt, HubSpot and Salesforce data structures, SaaS metrics (ARR, churn, CAC, LTV), and Looker Studio or another BI tool.