Lead Data Engineer

Job requirements

• Strong technical leadership in implementation or data engineering contexts.

• Excellent problem-solving skills in complex, distributed system environments.

• Strong client-facing communication skills with the ability to translate technical topics into clear explanations. Ability to work effectively in fast-paced, customer-driven environments.

• Ability to design and optimize data pipelines and ETL workflows.

• Strong ownership mindset with the ability to drive issues to resolution.

• Collaboration skills across engineering, product, and client-facing teams.

• 6+ years of experience in Data Engineering, Software Engineering, or a related technical field.

• Expert-level Python development experience.

• Proven experience designing and maintaining large-scale ETL pipelines and data workflows.

• Strong hands-on experience with AWS cloud environments and with Apache Airflow for workflow orchestration.

• Experience working with distributed systems and production-grade deployments.

• Experience in client-facing technical roles, such as implementation, consulting, or solution engineering.

• Experience working with financial services, trading systems, or time-series data environments (preferred but not mandatory).

• Proven experience in people management or technical team leadership, including mentoring engineers, coordinating technical work within a team, and driving delivery execution.

• Strong written and verbal communication skills in English.

• Experience with Kubernetes and containerized deployments.

• Experience with OneTick or similar time-series / market data platforms.

• Familiarity with financial markets, market data workflows, or trading systems.

• Experience working with enterprise or institutional clients.

• Experience contributing to process improvements or delivery best practices.

Job responsibilities

• Lead the architecture, customization, and deployment ofOneTick-based solutions for financial market clients.

• Design, implement, andoptimizelarge-scale ETL workflows and data-processing pipelines.Participate in improving implementation practices, tools, and delivery processes within the team.

• Ensureperformance, reliability, and scalability of distributed deployments across AWS and client environments.