Head of Data

About Solidus Labs

At Solidus, we are shaping the financial markets of tomorrow by providing cutting-edge trade surveillance technology that protects investors, enhances transparency, and ensures regulatory compliance across traditional financial assets and crypto markets.

With over 20 years of experience in developing Wall Street-grade FinTech, our team delivers innovative solutions that financial institutions and regulators worldwide rely on to detect, investigate, and report market manipulation, financial crime, and fraud. Headquartered on Wall Street, with offices in Singapore, Tel Aviv, and London, we safeguard millions of retail and institutional entities globally, monitoring over a trillion events each day.

As an ambitious company in an extremely dynamic space, we pride ourselves on being independent, accountable, and organized, having a self-starter attitude, and being willing to get our hands dirty with day-to-day work that might be out of official scope — while never losing sight of the big picture.

The Role

We're looking for a Head of Data to lead our Tel Aviv-based Data organization — spanning Data Infrastructure, Data Applications, and Data Adapters/Integration. This is a group-lead role: you will own the org's technical direction and delivery end to end, manage a group of Tech Leads and Staff Engineers (not just individual contributors), and be the single accountable owner for how Solidus ingests, stores, serves, and scales data across billions of events a day.

This is a hands-on leadership role. You'll spend real time in code, architecture reviews, and incident debugging — not just in planning meetings — and you'll be expected to be physically present and available as the standard for how the org operates.

What you'll own

• Org leadership — manage and grow the Tech Leads and Staff Engineers running Data Infrastructure, Data Applications, and Data Adapters; set technical direction, hiring plans, and career paths for the group.
• Scale and reliability — guide decisions on our ClickHouse, Kafka, Airflow, and K8s-based pipelines processing billions of events a day across real-time and T+1 batch workloads; own migrations and technical-debt paydown (e.g., decommissioning legacy systems) with a concrete, tracked plan.
• End-to-end technical accountability — own architecture and detailed design decisions across the data stack; personally review critical PRs and lead debugging on high-severity production issues rather than delegating and disengaging.
• Delivery and quality — drive sprint delivery, on-call health, testing rigor, and code-review discipline across all three teams; be the last line of defense against regressions and breaking changes reaching production.
• Cross-functional and external representation — partner with Product, Compliance, Customer Success, and clients on integrations and data quality; represent the Data org professionally and constructively in stakeholder-facing conversations, including under pressure.
• Team development — mentor and coach Tech Leads and engineers, give and receive feedback directly and without defensiveness, and build clear upward paths for high performers.
  
  

• 8+ years of backend/data engineering experience, including 3+ years managing multiple teams or leading through Tech Leads/Staff Engineers (not just individual contributors).
• Genuinely hands-on: Read and review code, help debug production issues personally, and go deep on a system rather than relying on secondhand summaries.
• Experience with high-throughput, low-latency data systems at scale: streaming (Kafka or similar), analytical stores (ClickHouse, Snowflake, or similar), orchestration (Airflow), and containerized microservices (K8s).
• Strong SQL and query optimization experience; comfort owning schema versioning, data governance, and deduplication strategy at scale.
• Proven track record of end-to-end ownership — architecture through implementation through operational health — with a demonstrated habit of catching issues (code review, testing, monitoring) before they reach production.
• Experience with monitoring and observability tooling (Prometheus, Grafana, Datadog, or similar) and owning operational SLAs.
• Demonstrated reliability and availability as a leadership default — consistent, predictable presence; transparent, advance planning of time off/travel rather than after-the-fact notice.
• Clear, professional written and verbal communication with both engineering and non-engineering/external stakeholders, including a demonstrated pattern of incorporating critical feedback without defensiveness.
• AI fist: coding tools/harnesses as part of a modern engineering workflow.
• Domain experience in fintech, trading, or crypto compliance/surveillance.
• Experience integrating third-party/customer data sources or leading vendor-facing technical relationships.