Senior Data Engineer

We seek a dynamic and talented Data Engineer to join our data team. The ideal candidate should have a strong background in data engineering, with a preference for those with a finance background. You will play a pivotal role in our data infrastructure, working closely with data scientists and analysts to ensure optimal data delivery throughout ongoing projects.

This is your mission

• Design, construct, and maintain scalable data processing systems.
• Develop ETL processes to support the business’s reporting and analytics development, validation, and deployment.
• Collaborate closely with ML engineers and data scientists to gather requirements and implement complex data solutions to ensure optimal data delivery for model training and inferencing.
• Engineer features from raw data for ML models, ensuring data quality and integrity.
• Optimize and maintain our data pipelines, ensuring data integrity and timely data refreshes.
• Develop set processes for data mining, data modeling, and data production.
• Design and implement data applications and solutions in the financial domain, ensuring accurate business intelligence representation.
• Create and maintain documentation for all database and ETL processes and workflows.
• Stay updated with emerging technologies and trends in the data engineering space.
• Monitor data pipeline performance, identify bottlenecks, and ensure the scalability of our ML solutions.
• Stay updated with the latest developments in data engineering, machine learning, and financial data processing.

What you bring along

• Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or a related field.
• Proficient understanding of distributed computing principles.
• Experience with big data tools: Hadoop, Spark, Kafka, etc.
• Proficiency with relational SQL and NoSQL databases, such as Postgres, Cassandra, and MongoDB.
• Strong understanding of ML algorithms and principles, with hands-on experience in feature engineering.
•  Familiarity with ML frameworks like TensorFlow, PyTorch, or Other.
•  Strong experience in building and optimizing data pipelines, architectures, and data sets.
• Experience in performing root cause analysis on internal and external data processes.

Nice to Have:

•  Background in finance, financial modeling, or a related domain.
•  Hands-on experience with financial platforms, and a clear understanding of financial data structures.

Your benefits