Data Engineering Lead

OANDA Corporation; Kraków; Hybrid; PLN 210,000 - 320,000; Full time

Benefits offered by this job

Hybrid work model

Office in Kraków

Job summary

OANDA Corporation in Kraków is seeking a Data Engineering Lead to guide a team responsible for designing, building, and scaling robust data platforms. You will bridge business needs with technical execution, shaping the data infrastructure and end-to-end data solutions.

The role emphasizes hands-on modernization of data infrastructure, overseeing Airflow pipelines, CI/CD practices, and rigorous testing to ensure reliable data delivery to stakeholders. Hybrid work model supported.

Qualifications

• 5+ years of hands-on experience in Data Engineering, Data Platform Administration, or DevOps.
• University / Post Graduate Degree (or equivalent working experience).
• Managerial Experience: 2+ years of proven experience supervising and mentoring technical team members.
• Infrastructure & Platform Administration: Strong proficiency in managing cloud data platforms, Airflow, automated CI/CD pipelines, and multi-tier environment (dev/stage/prod) setups.
• Architecture & Design: Deep understanding of data modeling, scalable architecture design, and infrastructure modernization.
• IT Implementation & Integration: Works independently to configure and optimize IT systems, ensuring smooth integration with existing infrastructure.
• Agile Planning & Execution: Ability to prioritize workloads, manage deployment cycles, and oversee team activities effectively to meet business objectives.
• Optimizes Work Processes: Drives continuous improvement in engineering practices, heavily focusing on automation, productivity, and deployment efficiency.
• Manages Complexity: Solves complex, high-quantity technical problems effectively and identifies underlying root causes.
• Ensures Accountability: Measures and tracks the team's performance, fostering a strong culture of ownership, high-quality delivery, and feedback.
• Communicates Effectively: Bridges the gap between technical teams and non-technical stakeholders, conveying information clearly and concisely.

Responsibilities

• Team Leadership & Direction: Lead, mentor, and support a team of data engineers, driving the successful delivery of business-critical data projects.
• Data Infrastructure Management: Oversee the design, architecture, and maintenance of scalable data platform infrastructures and cloud environments.
• Pipeline & Orchestration: Develop and optimize Apache Airflow, to build, monitor, and scale automated, high-performance data pipelines.
• CI/CD & Preproduction Environments: Implement and enforce rigorous CI/CD practices and comprehensive testing strategies, including unit, integration, and regression tests. Manage robust staging and preproduction environments to guarantee seamless, heavily tested, and reliable deployments to production.
• Architecture & Tooling Selection: Evaluate, select, and install appropriate data tooling based on evolving business needs. Ensure architectures align with industry best practices for data integrity and preservation.
• Operational Excellence: Lead on-call duties and incident management while proactively driving system improvements. Focus on implementing rigorous incident classification, collaborating with upstream teams to drive incident reduction, and leveraging testing and process enhancements to ensure long-term system reliability and stability.
• AI Champion: Act as an AI champion within the team, driving the adoption of AI agents for both software development and incident management, while ensuring that rigorous security and quality standards are maintained throughout the process.

Skills

Data engineering

Data platform admin

DevOps

Management

Cloud platforms

Airflow

CI/CD pipelines

Data modeling

Agile planning

Problem solving

Communication

Education

University degree

Job description

## Data Engineering LeadApply: Krakow: Full time: Posted Today: JR000910**Fancy helping to shape the future of FinTech?** We have always been innovators. In 1996 we were the first company to share exchange rate information, free of charge on the internet. Today, we are a world leading online trading group. **Join us to:*** Help build the future of online trading* Be part of a culture driven by integrity and global impact* Become part of an award-winning company - check out our full list of awards here **We are only as good as our people. Luckily, our people are the best. Join us!** **How do we work?**The Data Engineering Lead is responsible for leading the Data Engineering team to design, build, and scale robust data platforms. Bridging the gap between business needs and technical execution, you will drive end-to-end data solutions from requirements gathering to implementation. A core focus of this role is the hands-on modernization and management of our Data Infrastructure, emphasizing best practices across Airflow orchestration, CI/CD pipelines, and rigorous preproduction testing to ensure the reliable delivery of high-quality data to all stakeholders.We work in a hybrid model - we'd love to meet you in the office 2 times a week with respect to your own commitments.**In this role, you will:*** **Team Leadership & Direction:** Lead, mentor, and support a team of data engineers, driving the successful delivery of business-critical data projects.* **Data Infrastructure Management:** Oversee the design, architecture, and maintenance of scalable data platform infrastructures and cloud environments.* **Pipeline & Orchestration:** Develop and optimize Apache Airflow, to build, monitor, and scale automated, high-performance data pipelines.* **CI/CD & Preproduction Environments:** Implement and enforce rigorous CI/CD practices and comprehensive testing strategies, including unit, integration, and regression tests. Manage robust staging and preproduction environments to guarantee seamless, heavily tested, and reliable deployments to production.* **Architecture & Tooling Selection:** Evaluate, select, and install appropriate data tooling based on evolving business needs. Ensure architectures align with industry best practices for data integrity and preservation.* **Operational Excellence:** Lead on-call duties and incident management while proactively driving system improvements. Focus on implementing rigorous incident classification, collaborating with upstream teams to drive incident reduction, and leveraging testing and process enhancements to ensure long-term system reliability and stability.* **AI Champion:** Act as an AI champion within the team, driving the adoption of AI agents for both software development and incident management, while ensuring that rigorous security and quality standards are maintained throughout the process.**What skillset you need, to be successful in this role:*** 5+ years of hands-on experience in Data Engineering, Data Platform Administration, or DevOps.* University / Post Graduate Degree (or equivalent working experience).* **Managerial Experience:** 2+ years of proven experience supervising and mentoring technical team members.* **Infrastructure & Platform Administration:** Strong proficiency in managing cloud data platforms, Airflow, automated CI/CD pipelines, and multi-tier environment (dev/stage/prod) setups.* **Architecture & Design:** Deep understanding of data modeling, scalable architecture design, and infrastructure modernization.* **IT Implementation & Integration:** Works independently to configure and optimize IT systems, ensuring smooth integration with existing infrastructure.* **Agile Planning & Execution:** Ability to prioritize workloads, manage deployment cycles, and oversee team activities effectively to meet business objectives.* **Optimizes Work Processes:** Drives continuous improvement in engineering practices, heavily focusing on automation, productivity, and deployment efficiency.* **Manages Complexity:** Solves complex, high-quantity technical problems effectively and identifies underlying root causes.* **Ensures Accountability:** Measures and tracks the team's performance, fostering a strong culture of ownership, high-quality delivery, and feedback.* **Communicates Effectively:** Bridges the gap between technical teams and non-technical stakeholders, conveying information clearly and concisely.