Senior Data Engineer (with Java experience)
Location:
Remote from Spain (an indefinite Spanish contract)
Readinees for Business trips:
the final interview be conducted onsite in Frankfurt.
Our client is an independent and globally-established trading venue with more than 250 employees and more than 50 different nationalities worldwide. As Deutsche Börse Group’s FX unit, it provides a web-based trading technology for over-the-counter (OTC) instruments, integration solutions and related services. We stand for innovation in the FX market.
You will be part of the Software Development Unit and join one of our Change-the-System teams (CTS) according to your skills and interests. As a Senior Software Engineer, you take over ownership for projects from conception to final product. Your tasks will primarily revolve around building software by writing code, as well as modifying software to fix errors, adapt it to new hardware, improve its performance, or upgrade interfaces. You will also be involved in directing system testing and validation procedures and working with customers or departments on technical issues including software system design and maintenance.
Requirements:
- 5+ years of hands-on experience in data engineering with Java programming language and SQL.
- Experince with Flink, Spark - minimum 5 years
- Strong experience with ETL / ELT / orchestration tools (e.G., Airflow).
- Drive the design and implementation of data warehouse and data lakes.
- Proficient in code versioning (git) and building CI/CD for data projects.
- Experience with requirement gathering and documentation.
Will be a Plus:
- Experience with NoSQL.
- Experience with CDP, Python Kafka.
Responsibilities:
- Collaborate with business stakeholders and technical teams to understand and analyze data requirements.
- Lead the design and implementation of data models and database structures that meet business needs.
- Profile, refactor, and tune performance in the database.
- Design and implement complex ETL processes to extract, transform, and load data from various source systems into the data warehouse.
- Ensure data integrity, consistency, and accuracy through robust data quality assurance measures.
- Review and support team members, providing guidance and mentorship.
- Supervise and contribute to the data-driven strategy for the project, aligning it with business objectives.