We are looking for a Senior AI Data Platform Engineer to join our growing Data Infrastructure team!

The team's main responsibility is developing Voyantis' data platform - from building the microservices and pipelines that onboard customer data into our platform, to the infrastructure and tooling that enables our internal data teams to analyze, transform, process, and collect data independently. Our goal is to build leverage: every feature we ship reduces friction for the teams that depend on our platform. We're looking for a builder who takes full ownership from inception to production, cares deeply about quality and performance, and leverages AI tools to move faster and deliver better outcomes.

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 100 with offices in California, New York and Tel Aviv.

• Design and implement scalable, production-grade data pipelines and microservices that ingest, transform, and move data from a wide variety of customer sources at high volume.
• Build and maintain high-performance backend services and APIs that interface with our data ecosystem, ensuring reliability, low latency, and security.
• Develop and evolve the platform infrastructure — data warehouse, orchestration, compute — that internal data teams rely on daily.
• Identify opportunities to automate recurring workflows and turn ad-hoc needs into robust, self-serve platform capabilities.
• Collaborate with data scientists, analysts, and engineers across R&D to translate requirements into platform features.
• Drive code quality through design reviews, code reviews, and adherence to engineering best practices.
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• Leverage AI tools throughout the full engineering cycle — from scoping and design to implementation and debugging — to deliver faster, higher-quality outcomes.

• 5+ years of software engineering or data engineering experience, building production systems at scale.
• Strong software engineering fundamentals — clean code, testing, microservices design, API development.
• Deep understanding of data — modeling, pipelines, ETL/ELT processes, and query optimization.
• Proven experience with cloud environments, primarily AWS.
• Experience with modern data warehouses such as Snowflake / Databricks and orchestration tools such as Airflow / dbt.
• Strong SQL skills and experience working with large-scale datasets.
• Proven ability to take ownership end-to-end: from gathering requirements and designing solutions to deployment and production support.
• Hands-on experience using AI coding tools (Cursor, Claude Code, or similar) as a core part of the engineering workflow.
• Proactive by nature with a strong sense of ownership and internal drive for excellence.
• Excellent written and verbal communication skills; high English proficiency.
• Bachelor's degree in Computer Science, Engineering, or equivalent experience.