Data Engineer building data solutions using SQL, Python, and AWS for fintech. Focused on ETL processes and big data technologies to meet business needs.
Responsibilities
Assemble large, complex datasets that meet functional and non-functional business requirements;
Build the infrastructure and delivery solutions required for data extraction, transformation, and loading (ETL), suitable for a wide variety of data sources using PySpark, SQL, AWS and Databricks;
Create diagrams for proposed technical solutions, such as data models, data flows, deployment diagrams, etc.;
Strong programming experience in Python or other object-oriented languages for big data processing;
Design, build, and maintain scalable data pipelines and related data access patterns using big data tools and languages;
Research, evaluate, and adopt new technologies, tools, and frameworks focused on high-volume data processing.
Requirements
Education: Bachelor's degree in Business Administration with specialization or a solid background in Information Systems, Systems Analysis, Computer Science, Software Engineering, Statistics, or Mathematics.
Data analysis skills;
Experience writing SQL queries;
Experience programming in Python;
Knowledge of PySpark for Big Data processing;
Familiarity with the Databricks platform;
Knowledge of Data Modeling;
Experience with AWS and cloud technologies as a whole;
Results-oriented with excellent communication and interpersonal skills;
Adherence to secure development best practices;
Business awareness, focused on building value-driven solutions for customers;
Proactivity;
Initiative;
Experience and understanding of Agile methodologies.
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