Data Engineer

Key Responsibilities:

Data Infrastructure Development:

• Design, develop, and maintain scalable data pipelines and systems for collecting, storing, and processing large sets of structured and unstructured data.
• Ensure data architecture aligns with business requirements and industry best practices.
• Implement and manage ETL (Extract, Transform, Load) processes to integrate data from various sources into a centralized data warehouse.

Database Management:

• Maintain and optimize databases (e.g., SQL, NoSQL) for performance, reliability, and scalability.
• Implement data models, schemas, and queries to support data analysis and reporting needs.
• Monitor database performance, troubleshoot issues, and optimize queries for efficiency.

Data Integration:

• Collaborate with data scientists, analysts, and business units to understand data requirements and deliver solutions.
• Develop and maintain APIs and data integration workflows to enable seamless data sharing across systems.
• Ensure data quality, integrity, and security throughout the data lifecycle.

Big Data Technologies:

• Utilize big data technologies (e.g., Hadoop, Spark, Kafka) to handle large-scale data processing and real-time data streaming.
• Develop and manage data lakes and other big data solutions to support advanced analytics and machine learning initiatives.

Data Governance & Compliance:

• Implement and enforce data governance policies and best practices to ensure data privacy, security, and compliance with regulatory requirements (e.g., GDPR, CCPA).
• Maintain documentation and metadata for data assets to ensure transparency and traceability.

Continuous Improvement:

• Stay current with emerging data engineering technologies and methodologies.
• Identify opportunities for process improvements and implement innovative solutions to enhance data infrastructure and workflows.
• Participate in code reviews and contribute to a collaborative team environment.

Required Qualifications:

• Bachelor’s degree in Computer Science, Information Technology, or a related field; Master’s degree preferred.
• Proven experience as a Data Engineer or in a similar role within the banking or financial services industry.
• Proficiency in programming languages (e.g., Python, Java, Scala) and data processing frameworks.
• Strong knowledge of SQL and experience with relational and non-relational databases.
• Experience with cloud platforms (e.g., AWS, Azure, Google Cloud) and related services.
• Familiarity with big data technologies (e.g., Hadoop, Spark, Kafka).
• Understanding of data warehousing concepts and ETL processes.
• Excellent problem-solving skills and attention to detail.
• Strong communication and collaboration skills.

Preferred Qualifications:

Experience with data governance and regulatory compliance in the banking sector.

Knowledge of data visualization tools (e.g., Tableau, Power BI).

Experience with machine learning and data science workflows.

Certifications in relevant technologies or cloud platforms.