We are seeking a Senior Data Engineer to design, develop, and maintain the data infrastructure that supports the organization's AI, machine learning, and analytics initiatives. Working closely with data scientists, ML engineers, and business stakeholders, the Senior Data Engineer will be responsible for building scalable, reliable data pipelines and ensuring data is accessible, consistent, and production-ready across the organization.
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Key Responsibilities
- Design, construct, install, test, and maintain highly scalable data pipelines with a focus on machine learning models and analytics
- Work closely with data scientists, ML engineers, and stakeholders to ensure data is accessible, consistent, and reliable for ongoing projects
- Develop and maintain APIs for data access and manipulation, and integrate with external data services as needed
- Manage and optimize data storage solutions for both structured and unstructured data, including relational databases, NoSQL databases, search engines such as Elasticsearch, and object storage
- Implement data quality monitoring processes to ensure production data is always accurate and available to key stakeholders
- Collaborate with ML engineers on data-related technical issues and provide architectural guidance and solutions
- Support metadata management and data governance using cataloging tools such as OpenMetadata
- Ensure compliance with data security and privacy policies across all data systems
- Maintain clear and up-to-date documentation including data dictionaries, metadata, and architectural diagrams
- Contribute to real-time and streaming data processing requirements where applicable
Requirements
- Bachelor's degree in Computer Science, Engineering, Mathematics, or a related field, or equivalent professional experience
- 8 or more years of experience in a data engineering role
- Proficiency in Python, Java, and Scala, with experience managing large-scale data at terabyte to petabyte scale
- Hands-on experience with big data technologies including Hadoop, Spark, and Flink
- Familiarity with machine learning frameworks such as TensorFlow, PyTorch, or similar
- Strong understanding of data warehousing, ETL processes, and data modeling concepts
- Experience with cloud platforms, with AWS as the primary platform including S3, Redshift, Glue, and Lambda; Azure, GCP, and VMware experience is beneficial
- Experience with API development using RESTful or GraphQL approaches
- Knowledge of DevOps practices, CI/CD, and containerization using Docker or Kubernetes
- Familiarity with BI tools such as Metabase and data catalog tooling such as OpenMetadata
- Experience with streaming platforms such as Kafka or RabbitMQ
- Fintech sector experience is an advantage
Technical Skills
- Languages: Python, Java, Scala, SQL, Bash
- Big Data: Hadoop, Spark, Flink
- Unstructured Data: Text, Image, Audio, and Video
- Databases: MySQL, PostgreSQL, MongoDB, Cassandra, HBase, Redis
- Cloud: AWS (S3, Redshift, Glue, Lambda) as primary; Azure, GCP, VMware
- APIs: RESTful, GraphQL, OpenAPI
- Data Services: Kafka, RabbitMQ
- Containers: Docker, Kubernetes
- BI and Cataloging: Metabase, OpenMetadata
Work Conditions
- Competitive salary plus performance-based incentives
- Access to a dynamic, international, and fast-growing environment
- Strong opportunities for career progression within a global financial group
- Be part of a business committed to innovation, excellence, and long-term growth
The company is an equal opportunity employer. We welcome applications from candidates of all backgrounds and do not discriminate on the basis of nationality, gender, age, religion, or disability.
