Senior Data Engineer
- Tel Aviv District, Israel
במבט מהיר
- ניסיון
- 5+ שנים
- תפקיד
- מהנדס נתונים
נכון ל‑2026-11-03, סקאוטר עוקב אחר 107 משרות מהנדס נתונים פתוחות בישראל, שנאספות כל בוקר מלוחות הדרושים ומאתרי הקריירה של החברות.
תיאור
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. Description 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.