Senior Data Engineer
Location: Tel Aviv, Israel (תל אביב) · Category: R&D · Seniority: Senior · Work model: Hybrid · Posted: 2026-05-18
The company
We are a fast-growing B2C entertainment startup building a mobile-first streaming product for on-demand viewing. We pair original content with a data- and AI-led discovery experience, and we are scaling quickly with a large and growing international audience.
The Role
A Senior Data Engineer to become the backbone of data-driven decision-making across the business. This is a high-impact role: you will design and maintain the entire data infrastructure, from raw event ingestion through to polished dashboards, giving the product, marketing and content teams real-time, actionable insight. You will own the full pipeline — modeling, transformation, visualization and automation.
Responsibilities
- Data pipeline architecture: design, build and maintain scalable ETL/ELT pipelines that ingest data from multiple sources into the data warehouse.
- Data modeling: design and maintain clean, well-documented data models that serve as the single source of truth for the organization.
- BI and analytics: build and own dashboards, reports and self-serve analytics tools that give real-time visibility into KPIs across acquisition, engagement, retention and monetization.
- Data quality and governance: implement monitoring, alerting and validation frameworks so data stays accurate, fresh and trusted across all pipelines and reports.
- Attribution analytics: support the marketing and growth teams with deep-dive analysis on campaign performance, ROAS, LTV modeling and attribution across paid and organic channels.
- Cross-functional partnership: work closely with product, marketing and content teams to translate business questions into data solutions, A/B test analysis and cohort studies.
Requirements
- BSc/BA in Computer Science, Engineering or a related field.
- At least 5 years of experience designing and building data pipelines, analytical tools and data warehouses.
- Strong Python and SQL skills.
- Practical experience building and maintaining ETL/ELT workflows using tools such as dbt and Airflow.
- Strong proficiency with modern BI platforms (Looker, Tableau, Power BI) — building dashboards, calculated fields and self-serve data products.
- Strong analytical thinking, with the ability to translate ambiguous business questions into clear data solutions and actionable insight.
- Experience with mobile attribution platforms (AppsFlyer, Adjust), product analytics tools (Mixpanel, Amplitude) and ad platforms (Meta Ads, Google Ads).
Advantages
- Experience analyzing in-app purchase economies, subscription funnels, reward systems and LTV models.
- Experience with content performance analytics or digital media data.
- Experience with Braze, Iterable or similar CRM and engagement platforms, and integrating their data into the warehouse.
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