Data Engineer

Roles and Responsibilities

Data Engineer

Overview:
We are seeking a Data Engineer with a strong background in Python, SQL, and AWS technologies. The ideal candidate will design and manage data pipelines, optimize databases, and develop to support financial processes, regulatory compliance, and business intelligence needs.

Key Responsibilities:

• Data Engineering & ETL: Design and implement data pipelines using AWS Glue for ETL, integrating data into AWS Redshift, and leveraging Amazon S3 for scalable, secure data storage.
• Database & Query Optimization: Manage and optimize relational databases (SQL Server, PostgreSQL, Oracle, My SQL) and AWS Redshift clusters, improving performance and writing complex SQL queries.
• Business Intelligence Development: Create BI dashboards and reports using tools like Tableau, providing insights on financial, risk, and customer behavior metrics.
• Python Development: Develop scripts for data automation, manipulation, and integration with financial systems, utilizing libraries like Pandas, NumPy, and SQLAlchemy.
• Cross-functional Collaboration: Work with finance, risk, and operations teams to ensure data management aligns with business goals and regulatory compliance.

Qualifications:

• Education: Bachelors or Masters degree in Computer Science, Data Engineering, Information Systems, or a related field.
• Experience: 2+ years in data engineering and BI development, preferably within the NBFC/Banking industry.

Technical Skills:

• Proficiency in Python for data manipulation and automation.
• Strong SQL and relational database management experience.
• Expertise in AWS technologies (S3, Glue, Kafka, Athena, Lambda).
• Familiarity with data warehouse solutions (Redshift) and BI tools like Tableau.
• Knowledge of banking and financial regulations is a plus.

Other Skills:
Strong analytical mindset, attention to detail, problem-solving skills, and ability to work independently.