Data Engineer: Pipelines, Spark & Fabric

BM Global Services Buenos Aires; Buenos Aires; Presencial; ARS 2.400.000 - 4.200.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Exclusive discounts

Employee Assistance Program

Back-to-School Benefits

Family Care Leave

Tuition support

LinkedIn Learning

Free English courses

University discounts

Descripción de la vacante

BM Global Services Buenos Aires, part of Baker McKenzie’s global network, seeks a Data Engineer to design and implement data solutions primarily within Microsoft Fabric. You will build scalable pipelines and Spark notebooks to transform and deliver data across our enterprise environment.

The role requires 5–6 years of data engineering experience, strong Python and T-SQL skills, and the ability to work with diverse data types.

Formación

• 5–6 years of direct data engineering experience.
• Strong hands-on experience with Python.
• Experience with T-SQL.
• Experience building data pipelines and Spark notebooks.
• Experience working with structured, semi-structured, and unstructured data.
• Ability to communicate and collaborate effectively in English.

Responsabilidades

• Design and develop data solutions primarily within Microsoft Fabric.
• Build, maintain, and optimize data pipelines and Spark notebooks.
• Develop data transformations using Python and T-SQL.
• Work with structured, semi-structured, and unstructured data.
• Implement data-quality checks and troubleshoot processing issues.
• Create documentation for data processes, solutions, and standards.

Conocimientos

Python

T-SQL

Data pipelines

Spark notebooks

Structured data

English communication

Herramientas

Microsoft Fabric

Snowflake

Databricks

Descripción del empleo

BM Global Services Buenos Aires, part of Baker McKenzie’s global network, seeks a Data Engineer to design and implement data solutions primarily within Microsoft Fabric. You will build scalable pipelines and Spark notebooks to transform and deliver data across our enterprise environment.

The role requires 5–6 years of data engineering experience, strong Python and T-SQL skills, and the ability to work with diverse data types.