Description:

Design, build, implement, and maintain data processing pipelines for ETL from various data sources.
Develop scalable solutions to transform data for analysis and enhance data flow for end-users.

Requirements:

6-8 years of experience in data engineering, focusing on financial systems on SaaS platforms.
Bachelor's or master's degree in computer science, Engineering, or a related field.
Deep expertise in Python, SQL, and distributed processing frameworks (e.g., Apache Spark, Databricks).
Proven experience with cloud-based data platforms (preferably AWS or Azure).
Strong understanding of data security, privacy, and compliance in financial services.
Experience with data orchestration tools (e.g., Airflow, dbt) and data warehouses (e.g., Snowflake, Redshift).
Familiarity with structured and semi-structured data formats (e.g., Delta, JSON, Parquet).

Skills