Who We're Looking For - The Team Lead & Architect
We’re looking for a hands-on Data Platform Team Lead to guide a high-performing team in designing, scaling, and operating the infrastructure that powers Chargeflow’s platform.
This role combines architectural leadership with people management. You’ll define the technical direction for our data platform while developing engineers, strengthening execution, and building a culture of ownership and technical excellence.
You’ll be responsible for the reliability, performance, security, and cost efficiency of data systems supporting millions of daily transactions and critical product, machine-learning, and analytics use cases. This is a role for someone who can move comfortably between long-term architecture, hands-on technical problem-solving, and day-to-day team leadership.
About Chargeflow
Chargeflow is a leading force in fintech innovation, tackling chargeback fraud and the impact it has on online businesses. Born from a deep passion for technology and eCommerce, we’ve developed an AI-driven solution that helps merchants manage credit card disputes, recover lost revenue, and protect their businesses through a unique success-based model.
Backed by $49M from Viola Growth, OpenView, Sequoia Capital, and other top-tier global investors, Chargeflow is on a product-led growth journey. We’re a tight-knit team of passionate builders and entrepreneurs, united by our mission to revolutionize eCommerce and protect online businesses from chargeback fraud.
The impact you’ll have
Build and evolve the data infrastructure that safeguards our clients’ revenue and powers critical product, ML, and analytics use cases.
Establish scalable engineering standards and operational practices (reliability, security, governance, and cost efficiency).
Lead and grow a team of data/infrastructure engineers while cultivating technical excellence and psychological safety.
What you’ll own (Your arena)
Leadership & MentorshipLead, mentor, and scale a team of talented data and infrastructure engineers.
Create strong execution rituals: clear ownership, high-quality delivery, feedback loops, and growth plans.
Data Infrastructure & FinOpsOwn the architecture and evolution of our modern data stack and platform services.
Drive cloud cost management (FinOps): cost visibility, optimization initiatives, and capacity planning.
High-Performance EngineeringOversee the design of distributed systems, real-time streaming, and batch pipelines capable of processing millions of daily transactions with minimal latency.
Define technical direction for storage, compute, and data movement patterns (event-driven + lakehouse).
Operational ExcellenceChampion Infrastructure-as-Code (IaC), CI/CD, and testing practices for infrastructure and data systems.
Establish observability standards (monitoring/alerting, SLOs, incident response, postmortems).
Partner on security compliance and data governance across the R&D organization.
Strategic CollaborationAct as the bridge between data engineering, product, data science, and core R&D teams to execute cross-functional initiatives.
Translate business goals into platform roadmaps, milestones, and measurable outcomes.
Requirements
What You Bring
Experience: 6+ years in data platform engineering, data infrastructure, or backend engineering, including 2+ years leading/managing/mentoring engineers.
Strong software engineering: Proficiency in Python (or similar) and modern practices (clean code, CI/CD, testing paradigms).
Data architecture: Extensive experience architecting and operating scalable data lakes/lakehouses, distributed systems, and real-time event-driven architectures.
Cloud-native & IaC: Experience with AWS, GCP, or Azure, plus Docker/Kubernetes and Infrastructure-as-Code (e.g., Terraform).
Databases & storage: Strong knowledge of relational (e.g., PostgreSQL), NoSQL, and analytical databases, including performance optimization, schema design, and cost tuning at scale.
Execution & delivery: Proven track record managing sprint planning, scoping technical projects, and delivering complex infrastructure roadmaps on time.
Nice to Have
Advanced data stack: Apache Iceberg (Lakehouse/S3/Glue), Apache Spark optimization, and big data processing.
Streaming & messaging: Kafka, Kinesis, Flink, Kafka Streams.
Modern tooling: Temporal/Dagster, dbt/DuckDB, Datadog/Grafana, Pydantic.
FinOps & governance: Spot instances/savings plans and compliance frameworks (GDPR/PCI-DSS).
How We Work
We move quickly, collaborate across disciplines, and expect leaders to take ownership of both technical outcomes and team development. Our Team Leads remain close to the architecture and the work while creating the clarity, standards, and environment their teams need to succeed.
We care about reliability and engineering excellence, but we also expect infrastructure decisions to support measurable product impact, operational efficiency, and sustainable scale.
This is a hybrid role based in our Modi’in office, with three days a week in the office.
If you’re looking for a leadership role where you can shape both a critical data platform and the team building it, we’d love to hear from you.
What You Bring
Experience: 6+ years in data platform engineering, data infrastructure, or backend engineering, including 2+ years leading/managing/mentoring engineers.
Strong software engineering: Proficiency in Python (or similar) and modern practices (clean code, CI/CD, testing paradigms).
Data architecture: Extensive experience architecting and operating scalable data lakes/lakehouses, distributed systems, and real-time event-driven architectures.
Cloud-native & IaC: Experience with AWS, GCP, or Azure, plus Docker/Kubernetes and Infrastructure-as-Code (e.g., Terraform).
Databases & storage: Strong knowledge of relational (e.g., PostgreSQL), NoSQL, and analytical databases, including performance optimization, schema design, and cost tuning at scale.
Execution & delivery: Proven track record managing sprint planning, scoping technical projects, and delivering complex infrastructure roadmaps on time.
Nice to Have
Advanced data stack: Apache Iceberg (Lakehouse/S3/Glue), Apache Spark optimization, and big data processing.
Streaming & messaging: Kafka, Kinesis, Flink, Kafka Streams.
Modern tooling: Temporal/Dagster, dbt/DuckDB, Datadog/Grafana, Pydantic.
FinOps & governance: Spot instances/savings plans and compliance frameworks (GDPR/PCI-DSS).
How We Work
We move quickly, collaborate across disciplines, and expect leaders to take ownership of both technical outcomes and team development. Our Team Leads remain close to the architecture and the work while creating the clarity, standards, and environment their teams need to succeed.
We care about reliability and engineering excellence, but we also expect infrastructure decisions to support measurable product impact, operational efficiency, and sustainable scale.
This is a hybrid role based in our Modi’in office, with three days a week in the office.
If you’re looking for a leadership role where you can shape both a critical data platform and the team building it, we’d love to hear from you.
