Senior Data Engineer

Fynapse, a pioneering finance data and accounting platform, is in the process of developing a Modern Data Stack and is seeking a highly skilled Data Engineer to lead this transformation. The role involves building from the ground up - including data lakes, data warehouses, and implementing tools for data transformation and orchestration. We're looking for someone passionate about creating efficient, scalable data solutions and eager to play a pivotal role in the evolution of our AI-driven finance technology.

Responsibilities

• Design and implement robust data architectures, including data lakes and data warehouses, from scratch.
• Identify and integrate tools for data transformation and orchestration to streamline data flow and processing.
• Collaborate with IT and software development teams to assess and deploy new technologies and tools.
• Ensure optimal data processing architectures are in place for both real-time and batch data processing.
• Manage the collection, storage, and retrieval of large datasets, ensuring scalability, reliability, and security.
• Develop and maintain scalable and efficient data pipelines.
• Work closely with data analysts and other stakeholders to understand data needs and deliver solutions that meet business requirements.
• Integrate new data sources into the data platform through APIs or bulk data transfer.
• Stay abreast of industry trends and best practices in data engineering.
• Develop and manage data pipelines for both batch and real-time data processing, with a focus on streaming data handling using Kafka.

We’ll also offer you a competitive salary plus profit-related bonus scheme, as well as the following benefits:

• Profit-related bonus
• Private healthcare
• Life and disability insurance
• ShareSave scheme - ability to purchase company shares on preferential terms
• English language lessons during working hours
• Flexible working conditions and hybrid work model

The ideal candidate will have the following skills & experience:

• Bachelor's or Master's degree in Computer Science, Engineering, or related field.
• 4+ years of experience in data engineering, including hands-on experience in building data lakes and data warehouses.
• Strong experience in streaming data platforms, particularly Kafka.
• Proficiency in SQL and experience with relational and NoSQL databases.
• Experience in implementing data processing pipelines and ETL processes.
• Strong programming skills in Python.
• Understanding of Java, Scala.
• Solid understanding of big data technologies (such as Hadoop, Spark) and cloud services (AWS, Azure, GCP).
• Excellent problem-solving and analytical skills.
• Ability to work independently and manage multiple projects simultaneously.

Preferred Qualifications

• Experience in setting up data transformation tools.
• Familiarity with orchestration tools and their implementation.
• Knowledge of finance and accounting principles is a plus.
• Proven track record of successful project management in data engineering.