Data Infrastructure Team Lead
Indexed description
Who We're Looking For — The Team Lead & Architect
We are seeking an experienced Data Engineering / Data Infrastructure Team Lead to guide a high-performing team in designing, scaling, and managing the robust, cost-efficient infrastructure powering our solution.
In this role, you will balance technical excellence with people leadership. You will architect distributed data systems and cloud-native technologies to safeguard our clients' revenue while driving strategic initiatives that align with business objectives, operational efficiency, and team growth.
Our ultimate goal is to equip our clients with resilient safeguards against chargebacks, empowering them to optimize their profitability. Join us on this thrilling mission to redefine the battle against fraud.
Your Arena
- Leadership & Mentorship: Lead, mentor, and scale a team of talented data and infrastructure engineers. Cultivate a culture of technical excellence, continuous learning, and psychological safety.
- Data Infrastructure & FinOps: Own the architecture and evolution of our modern data stack, ensuring robust, scalable backend services while driving cloud cost management (FinOps) to maximize resource efficiency.
- High-Performance Engineering: Oversee the design of distributed systems, real-time streaming, and batch pipelines capable of processing millions of daily transactions with minimal latency.
- Operational Excellence: Champion Infrastructure-as-Code (IaC), rigorous security compliance, data governance, and deep observability (monitoring/alerting) across the R&D organization.
- Strategic Collaboration: Act as the bridge between data engineering, product, data science, and core R&D teams to execute complex cross-functional initiatives.
What It Takes — Must-Haves
- Experience: 6+ years of experience in data platform engineering, data infrastructure, or backend engineering, with at least 2+ years of experience leading, managing, or mentoring a team of engineers.
- Language Proficiency: Strong proficiency in Python (or similar languages) and advanced software engineering principles (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, alongside hands-on experience with containerization (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 of managing sprint planning, scoping technical projects, and delivering complex data infrastructure roadmaps on time.
- Advanced Data Stack: Experience with Apache Iceberg (Lakehouse/S3/Glue), Apache Spark (Optimization), and Big Data processing.
- Streaming & Messaging: Experience with Kafka, Kinesis, Flink, or Kafka Streams.
- Our Tech Stack Components: Orchestration (Temporal/Dagster), Modern Data Stack (dbt/DuckDB), Observability (Datadog/Grafana), Pydantic.
- FinOps & Governance: Hands-on cloud cost optimization (Spot instances, savings plans) and Data Governance compliance (GDPR/PCI-DSS).
Backed by $49M led by Viola Growth, OpenView, Sequoia Capital, and other top-tier global investors, Chargeflow has embarked on a product-led growth journey. Today, we represent a tight-knit community of passionate individuals and entrepreneurs, united in our mission to revolutionize eCommerce and fight against chargeback fraud, marking us as pioneers in protecting online business revenues.
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