דרושים Senior Data Engineer בתל אביב

We are looking for a Senior Data Engineer to join our Data Hub team.

The team develops Voyantis Data Platform—a strategic enabling layer that provides tooling and infrastructure. It allows our data consumers (Analytics Engineers, ML Engineers, and future AI agents) to securely manage and process massive data volumes, which directly powers our core product offering.

In this role, You will be a key player in our ambitious transition to a Gen-AI-powered data ecosystem, where manual data flows are replaced by autonomous agents. We are looking for an engineer who thrives on technical ownership, can drive impact from inception to production, and is comfortable wearing a product hat when needed, running on a feature from concept to delivery.

About Us

Voyantis was founded in 2020 on the premise that market fundamentals are shifting companies worldwide from growth-at-all-costs strategies to efficient and responsible growth practices, with a focus on improving Unit Economics. With a bold mission to leverage AI to reimagine the whole Growth process, to streamline this transition and ensure its sustainability, Voyantis eliminates the guesswork from customer value creation, empowering leaders with actionable strategies and tactics to acquire, nurture and retain the high-value customers their businesses really need, with the actions and the timing that would be most impactful to achieve their goals.

Leading companies like Miro, Rappi and Moneylion rely on Voyantis to effectively apply these predictions. They use Voyantis to drive high-value customer acquisition on platforms like Google and Meta, optimize incentives through Salesforce and Braze, and perfectly time upsells, resulting in a 20%-40% ROI uplift.

Voyantis is well-backed by top VCs such as Target Global and SquarePeg. The company has tripled in size annually over the past two years and now boasts a team of 70 with offices in California, New York and Tel Aviv.

Responsibilities:

• Platform Abstraction & Tooling: Design and implement high-quality, large-scale cloud data infrastructure, self-service tooling, and microservices that abstract complexity. This enables data users to build their own pipelines and transformation logic efficiently.
• Infrastructure Ownership: Own the underlying AWS infrastructure and services, ensuring optimized performance, scalability, reliability, and cost-efficiency (FinOps) for our batch workloads.
• Governance Engineering: Design and implement platform features that enforce strict operational concerns, including Data Quality, Data Security, Compliance, and Data Governance programmatically.
• Collaborate with cross-functional teams, including analysts, data scientists, and product managers, to gather requirements and define the platform roadmap.
• Drive and coordinate cross-R&D product workflows and initiatives.
• Participate in code reviews and ensure adherence to coding standards and best practices.

Requirements:

• BSc in Computer Science, Engineering, or equivalent.
• 5+ years of hands-on experience in Platform Engineering, Software Engineering, or Data Infrastructure roles, focusing on building large, complex, and scalable data infrastructures.
• Solid understanding of Big Data paradigms (distributed systems, partitioning, data modeling) and experience optimizing performance in data warehouses like Snowflake (or similar).
• Strong proficiency in a programming language (Python preferred) for building scalable backend services.
• Deep experience with AWS infrastructure and services that support data platforms.
• Experience implementing operational platform features related to Data Governance, Data Security, FinOps, and Data Quality.
• Solid understanding of software design principles (concurrency, synchronization, memory management, data structures, cost analysis).
• A high degree of autonomy, a strong sense of ownership, and the ability to drive technical initiatives independently.
• Work Model: Hybrid (4 days per week in the office)

Advantage

• Experience or strong interest in applied Generative AI for data automation.
• Experience with containers and orchestration (Docker, Kubernetes).
• Deep experience with SQL.
• Experience with self-service transformation tools like dbt.
• Experience with Frontend development (e.g., React, Angular) as we build the platform's UI end-to-end.