Data Engineering Team Lead – Recommendations Platform

Description Here at Lusha, we power sales with data. Over 1.5M users and teams at Google, Spotify, and Elastic use our platform to find verified contacts, spot real-time buying signals, and automate workflows with 200M+ records. As a Data Engineering Team Lead - Recommendation Platform, you’ll lead a team of Data Experts responsible for building and scaling the infrastructure, pipelines, and systems that power Lusha’s similarity and recommendation engine. You’ll guide the design, implementation, and optimization of our data layer, working closely with data scientists and product teams to deliver fast, accurate, and personalized recommendations used by thousands of users every day. Data is at the core of everything we do at Lusha. In this role, you’ll own the engineering backbone that enables our data engineers & data scientists to experiment, innovate, and deploy production-ready models, ensuring our systems are robust, scalable, and future-proof.

What You'll Actually Do:

• Lead and mentor a team of Data Engineers, fostering a culture of technical excellence, accountability, and collaboration.
• Define and drive the team’s technical roadmap, standards, and best practices for data modeling, performance, and reliability.
• Design, build, and evolve scalable embedding pipelines and recommendation infrastructure, from algorithm tuning and training workflows to production deployment.
• Manage and optimize vector db, ensuring efficient indexing strategies, search performance, and low-latency retrieval.
• Lead the development of retrieval services leveraging Approximate Nearest Neighbor (ANN/KNN) techniques such as HNSW, IVF, and Product Quantization (PQ).
• Ensure reliability, observability, and scalability across all real-time data systems powering our recommendation engine.
• Collaborate with Data Science, Product, and Analytics to operationalize models, validate KPIs, and translate technical insights into actionable product improvements.

Requirements 3+ years of experience leading data engineering teams. 5+ years of hands-on experience developing large-scale data and ML systems, with strong foundations in distributed computing, data pipelines, and algorithm development.

• Strong programming skills in Python, with practical experience using modern data and ML frameworks such as Spark, Airflow, MLflow, or equivalent technologies.
• Proven experience designing and maintaining embedding pipelines, feature stores, and model-serving infrastructure.
• Excellent leadership and communication skills, with a passion for mentoring engineers and driving technical excellence.
• Ability to translate complex technical challenges into scalable, reliable engineering solutions.

Bonus Points For:

• Experience building or operating real-time data retrieval, personalization, or search systems.
• Knowledge of Elasticsearch, Databricks, ClickHouse, or streaming architectures such as Kafka or Flink.

Why Lusha:

Founded in 2016 by Assaf Eisenstein and Yoni Tserruya, Lusha was built to revolutionize the B2B sales landscape. From a profitable bootstrap company to a $1.5B unicorn backed by $245M in investments, we’ve grown with an unwavering focus on innovation, simplicity, and trust. We’re trusted by thousands of companies worldwide — from startups to global enterprises like Google, Zendesk, and Yotpo. Our mission is to empower sales professionals to find the right people, at the right time, with the right insights — and we’re just getting started. We’re dreamers, innovators, and learners, driven by simplicity, collaboration, and trust. At Lusha, your work matters. Your voice is heard. And your growth is part of our growth. Ready to join us? Let’s build the future of sales, together.