Data Engineering Team Lead - Similarweb

Serve as the direct manager for data engineers, providing regular feedback, career guidance, and technical mentorship. Translate business requirements into actionable technical roadmaps; prioritize and assign daily tasks using sprint methodologies. Cultivate a collaborative, high-performance team culture focused on continuous improvement and engineering excellence. Cultivate a collaborative, high-performance team culture rooted in a delivery mindset, a business-driven focus, and engineering excellence. Design, build, and maintain robust, scalable data pipelines capable of processing massive datasets. Oversee and maintain multiple development and production environments to ensure seamless deployment and high availability. Design and implement highly cost-efficient cloud data infrastructure, constantly monitoring and optimizing resource utilization. Research, develop, and integrate AI models and autonomous agents into the data ecosystem to automate pipeline monitoring, optimize data curation, and unlock intelligent data-driven capabilities. 5+ years of experience in data engineering, with 2+ years in a leadership role. Strong hands-on experience handling massive datasets using PySpark, Spark, or Hadoop . Advanced proficiency in Python. Proven experience working within AWS (or alternative major cloud infrastructure). Practical experience working with LLMs, AI frameworks, or vector databases to build automated, agentic data workflows. Solid understanding of Docker and Kubernetes for containerizing and orchestrating data workloads. Experience managing complex, multi-stage development and production lifecycles Excellent interpersonal and communication skills with a natural ability to connect with, motivate, and mentor team members. Strong organizational skills with a track record of planning, scoping, and prioritizing team tasks effectively. A strategic thinker who can balance immediate operational needs with long-term infrastructure scalability and cost-efficiency.

Serve as the direct manager for data engineers, providing regular feedback, career guidance, and technical mentorship. Translate business requirements into actionable technical roadmaps; prioritize and assign daily tasks using sprint methodologies. Cultivate a collaborative, high-performance team culture focused on continuous improvement and engineering excellence. Cultivate a collaborative, high-performance team culture rooted in a delivery mindset, a business-driven focus, and engineering excellence. Design, build, and maintain robust, scalable data pipelines capable of processing massive datasets. Oversee and maintain multiple development and production environments to ensure seamless deployment and high availability. Design and implement highly cost-efficient cloud data infrastructure, constantly monitoring and optimizing resource utilization. Research, develop, and integrate AI models and autonomous agents into the data ecosystem to automate pipeline monitoring, optimize data curation, and unlock intelligent data-driven capabilities. 5+ years of experience in data engineering, with 2+ years in a leadership role. Strong hands-on experience handling massive datasets using PySpark, Spark, or Hadoop . Advanced proficiency in Python. Proven experience working within AWS (or alternative major cloud infrastructure). Practical experience working with LLMs, AI frameworks, or vector databases to build automated, agentic data workflows. Solid understanding of Docker and Kubernetes for containerizing and orchestrating data workloads. Experience managing complex, multi-stage development and production lifecycles Excellent interpersonal and communication skills with a natural ability to connect with, motivate, and mentor team members. Strong organizational skills with a track record of planning, scoping, and prioritizing team tasks effectively. A strategic thinker who can balance immediate operational needs with long-term infrastructure scalability and cost-efficiency.

Serve as the direct manager for data engineers, providing regular feedback, career guidance, and technical mentorship. Translate business requirements into actionable technical roadmaps; prioritize and assign daily tasks using sprint methodologies. Cultivate a collaborative, high-performance team culture focused on continuous improvement and engineering excellence. Cultivate a collaborative, high-performance team culture rooted in a delivery mindset, a business-driven focus, and engineering excellence. Design, build, and maintain robust, scalable data pipelines capable of processing massive datasets. Oversee and maintain multiple development and production environments to ensure seamless deployment and high availability. Design and implement highly cost-efficient cloud data infrastructure, constantly monitoring and optimizing resource utilization. Research, develop, and integrate AI models and autonomous agents into the data ecosystem to automate pipeline monitoring, optimize data curation, and unlock intelligent data-driven capabilities. 5+ years of experience in data engineering, with 2+ years in a leadership role. Strong hands-on experience handling massive datasets using PySpark, Spark, or Hadoop . Advanced proficiency in Python. Proven experience working within AWS (or alternative major cloud infrastructure). Practical experience working with LLMs, AI frameworks, or vector databases to build automated, agentic data workflows. Solid understanding of Docker and Kubernetes for containerizing and orchestrating data workloads. Experience managing complex, multi-stage development and production lifecycles Excellent interpersonal and communication skills with a natural ability to connect with, motivate, and mentor team members. Strong organizational skills with a track record of planning, scoping, and prioritizing team tasks effectively. A strategic thinker who can balance immediate operational needs with long-term infrastructure scalability and cost-efficiency.