Senior Data Engineer
Vacancy ID: 129383
We are a multinational team of highly skilled professionals with a strong digital mindset. We take pleasure in creating new solutions that have a real impact on our clients' business. We are more than 4300 professionals with offices in Europe, the USA, Asia and LatAm.
Vacancy level: Senior
Cooperation type: Full-time
Technology stack: SQL, NoSQL, Spark, Hadoop, Kafka, ETL
Share the opportunity
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.
- Training budget
- KKM – monthly ticket (80% covered by us)
- MultiKafeteria (WorkSmile)
- Life Insurance (Generali)
- Private healthcare (LuxMed)
- Attractive Referral Program
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