Data Engineer

JD:

Please fill this table based on candidate experience and send

Skills Level Need Type

Control M Automation Intermediate Mandatory

PL/SQL Intermediate Mandatory

Postgres SQL Intermediate Mandatory

Jira Intermediate Mandatory

Credit Market Basic Desired

Apache Spark Basic Desired

This role seems like a great opportunity for someone with experience in data and a strong understanding of Big Data technologies, especially in the context of market risk. Below is how you could structure the tasks and requirements more clearly for a candidate interested in the position:

Responsibilities:

Process Definition and Automation:

Actively participate in the definition of processes related to data management within the Datahub of Markets.

Automate data tasks and processes using Big Data technologies (especially Spark and Scala).

Prepare the necessary data for system integration and ensure its quality.

Open requests following internal procedures for process automation and configuration.

Perform integrated testing and.collaborat, th the quality team to validate the execution of the process.

Collaboration in Market Risk Analysis:

Work with Market Risk teams to ensure that the data and models align with the needs of the risk department.

Collaborate in validating the accuracy and reliability of the data models used for risk analysis.

Requirements:

Technical Knowledge:

Advanced knowledge of SQL, especially in managing and analyzing large volumes of data.

Experience in data model design for efficient and scalable Big Data analysis.

Practical experience in performing data testing and validation to ensure process accuracy. ↓

Intermediate/advanced English to collaborate with international teams and understand technical documentation in English.

Desirable Skills (Not Required):

Technical knowledge of programming languages such as Scala and Big Data platforms like Spark, Hadoop.

Experience in technology projects in the banking sector, particularly in the area of financial risk analysis or data management.

Knowledge of financial products and market risk metrics, which can be useful for understanding data flows and the specific needs of the risk department.

This role seems more focused on process management and data quality rather than pure development, though technical knowledge is still valued, especially in the Big Data context. If you have experience in these areas and a good understanding of financial processes, this could be a great next step in your career within the field of risk analysis.

↓Role Description (in English)

Participation in the tasks of the Datahub of Markets to carry out tasks as a Data Engineer in the definition and automation of processes developed using Big Data technologies (Spark Scala) in Market Risk. The main functions will not be development-focused but rather process definition, data preparation, initiating requests following the department's procedures for automation and process configuration, integrated testing execution, and validation of the processes.

Requirements:

Advanced knowledge of SQL statements.

Experience in data model design.

↓

Experience in performing data testing and validation.

Intermediate/Advanced English proficiency.

Desirable (Not Mandatory):

Role Description (in English)

Participation in the tasks of the Datahub of Markets to carry out tasks as a Data Engineer in the definition and automation of processes developed using Big Data technologies (Spark Scala) in Market Risk. The main functions will not be development-focused but rather process definition, data preparation, initiating requests following the department's procedures for automation and process configuration, integrated testing execution, and validation of the processes.

Requirements:

Advanced knowledge of SQL statements.

Experience in data model design.

↓

Experience in performing data testing and validation.

Intermediate/Advanced English proficiency.

Desirable (Not Mandatory):Desirable (Not Mandatory):

Technical knowledge of programming languages (e.g., Scala) and platforms such as Spark, Hadoop.

Experience in technology projects in the banking sector.

Knowledge of financial products or market risk metrics.