As a Data Engineering Manager, you will lead the design, development, and optimization of scalable data pipelines and platforms. You will manage a team of data engineers, ensuring high standards of data quality, governance, and performance. Your role will be pivotal in aligning data engineering initiatives with business goals, fostering innovation, and driving operational excellence across the data lifecycle.

SKILLS AND QUALIFICATIONS:

Proven experience in managing data engineering teams and delivering complex data solutions.
Deep expertise in Big Data technologies (e.g., Spark, Hadoop) and cloud data platforms.
Advanced proficiency in programming (e.g., Python, Shell) and orchestration tools (e.g., Airflow, Docker).
Strong command of SQL and NoSQL databases (e.g., Oracle, HBase).
Experience with CI/CD pipelines, version control (e.g., Git, GitHub), and DevOps practices.
Excellent communication and stakeholder management skills.
Strategic thinking with a focus on scalability, performance, and maintainability.
Experience with Power BI for data visualization and reporting.
Strong understanding of Kimball star schema data modeling techniques.

EDUCATION AND EXPERIENCE:

Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
5+ years of experience in data engineering, with at least 2 years in a leadership role.
Demonstrated success in building and managing high-performing teams.
Our benefits reflects the FCA commitment to helping you reach your personal and professional goals. In addition to an environment that promotes career development, we offer benefits for a healthy lifestyle and a rewarding future, designed to take care of you and your family, in various stages of life.
As a global company, our employee packages will vary by country, customary norms and the legal entity into which you are hired

Lead and mentor a team of data engineers, providing technical guidance and career development.
Architect and oversee the implementation of robust, scalable data pipelines.
Ensure data integrity, quality, and compliance across all data engineering processes.
Collaborate with cross-functional teams to define data strategy, requirements, and delivery timelines.
Drive the adoption of best practices in data modeling, ETL/ELT design, and data platform optimization.
Implement and monitor end-to-end data workflows using modern orchestration and automation tools.
Evaluate and integrate emerging technologies to enhance data engineering capabilities.
Establish and enforce data governance, security, and privacy standards.