Data Team Lead/Head of Data Engineering

Head of Data Engineering & Infrastructure Bachelor’s degree in Computer Science or a related technical field 7+ years of data engineering experience, preferably in a startup or fast-paced technology company 4+ years of management experience, preferably in B2B2C, marketplace, SaaS, or consumer-scale environments Proven experience building and leading technical data teams, including data engineers, BI developers, and analysts Strong hands-on experience designing and scaling cloud data warehouses such as BigQuery or Snowflake Deep expertise in SQL, data modeling, ETL and ELT pipelines, orchestration tools such as Airflow, and analytics-ready data models Experience owning data quality, governance, event tracking, and company-wide source-of-truth systems Strong understanding of SaaS metrics, marketplace dynamics, and user behavior analytics Excellent communication skills with the ability to influence technical and business stakeholders at all levels Data Team Lead Management: 3+ years of experience leading a development team or serving as a Tech Lead for data/backend teams. Python Mastery: 4+ years of hands-on experience with Python (Must). Data Engineering: 5+ years of proven experience as a Big Data Backend or Data Engineer. Environments & Infrastructure: Deep understanding of Cloud environments alongside containerized On-Prem infrastructure (OpenShift, Kubernetes, Docker, Linux). Databases: Strong experience with SQL and NoSQL (PostgreSQL and OpenSearch/ElasticSearch – a significant advantage). Data Ops & CI/CD: Proven experience processing large-scale data sets and working with CI/CD methodologies (e.g., GitLab). Education: BSc/BA in Computer Science, Software Engineering, or a related field. ***** Senior Data Engineer - הפונקציה ראשונה בחברה BSc/BA in Computer Science, Engineering, or a related field. At least 5 years of experience with 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 (such as 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 insights. Experience working with mobile attribution platforms (AppsFlyer, Adjust), product analytics tools (Mixpanel, Amplitude), and ad platforms (Meta Ads, Google Ads).