Data Engineer
Job Description
- Design and develop scalable and robust data pipelines to ingest, process, and transform large volumes of data from various sources, including Oracle databases.
- Leverage your expertise in Oracle databases to optimize query performance, implement efficient indexing strategies, and fine-tune the data processing pipeline for enhanced data retrieval.
- Implement data modeling techniques to structure data in a way that optimizes performance and supports analytical needs.
- Build and maintain data warehouses, data lakes, and other storage systems, including Oracle-based solutions, to ensure efficient data storage, retrieval, and availability.
- Collaborate with data scientists and analysts to understand their data requirements and provide them with reliable and well-organized datasets for analysis and modeling, leveraging your Oracle experience to support complex financial data structures.
- Develop and maintain ETL (Extract, Transform, Load) processes, to integrate data from multiple sources into a unified format suitable for analysis.
- Optimize and tune data processing and storage systems, for improved performance, scalability, and reliability in financial services environments.
- Implement data governance and security measures, to ensure data integrity, confidentiality, and compliance with regulatory requirements in the financial services industry.
- Stay up to date with emerging technologies and industry trends in data engineering, and proactively propose innovative solutions to enhance our data infrastructure.
- Lead and mentor junior data engineers, providing technical guidance and sharing best practices for data engineering processes and technologies in Oracle and financial services contexts.
- Collaborate with cross-functional teams to identify and prioritize data engineering projects and initiatives that align with business goals and strategies in the financial services domain.
Job Requirements
- Bachelor’s or master’s degree in Computer Science, Engineering, or a related field.
- Proven experience as a Data Engineer or similar role, with a minimum of 6 years of hands-on experience in designing and implementing data solutions, preferably in the financial services industry.
- Strong programming skills in languages such as Python, Java, or Scala, with experience in working with data processing frameworks (e.g., Spark, Hadoop).
- Proficient in SQL and experience with relational and NoSQL databases.
- Solid understanding of data modeling concepts and experience with data modeling tools.
- Experience with cloud-based data technologies, such as AWS (Amazon Web Services), Azure, or Google Cloud Platform.
- Strong knowledge of data integration and ETL tools and techniques.
- Familiarity with data governance, data security, and privacy best practices, particularly in the context of financial services.
- Excellent problem-solving and analytical skills, with a strong attention to detail.
- Effective communication and collaboration skills, with the ability to work in cross-functional teams.
- Proven ability to lead and mentor junior team members.