Data Engineer

Ascendum System Private Limited; Argentina; Presencial; ARS 2.000.000 - 2.600.000; Jornada completa

Descripción de la vacante

Ascendum System Private Limited seeks a data engineering lead to collaborate with cross-functional teams and deliver scalable, secure data solutions. You will drive design and implementation of data pipelines using Kafka, Databricks, and NoSQL/SQL platforms, while promoting best practices and thorough testing.

The role emphasizes modernization of data assets, performance optimization, and mentorship within an agile environment, ensuring high-quality data engineering outcomes.

Formación

• Bachelor’s degree typically in Computer Science, MIS, Mathematics, Business Analytics or another STEM degree
• Proven experience working within cross-functional teams and managing complex projects from inception to completion
• 4+ years of professional Data Development experience
• 3+ years of experience with SQL and NoSQL technologies
• 3+ years of experience building and maintaining data pipelines and workflows
• 3+ years of experience developing with Python & PySpark
• Experience developing within Databricks
• Experience applying object-oriented design patterns and principles
• Experience with CI/CD pipelines and processes
• Experience with automated unit, integration, and performance testing
• Experience with version control software such as Git
• Full understanding of ETL and Data Warehousing concepts
• Strong understanding of Agile principles (Scrum)

Responsabilidades

• Provide technical leadership to ensure clarity between ongoing projects and facilitate collaboration across teams to solve complex data engineering challenges
• Build, design, and maintain scalable pipelines to support data ingestion, transformation, and integration across diverse sources using tools like Kafka and Databricks
• Drive innovation to modernize core data assets including SQL-based, NoSQL, cloud-based, and real-time streaming platforms
• Implement automated unit, integration, and performance testing frameworks to ensure data quality and compliance
• Optimize data workflows for performance, cost efficiency, and scalability across large datasets
• Mentor team members in data principles, patterns, processes, and practices to promote best practices
• Draft and review architectural diagrams, interface specifications, and design documents for clear communication

Conocimientos

Python

PySpark

SQL

NoSQL

Data Warehousing

Educación

Bachelor’s degree in Computer Science / MIS / Mathematics / STEM

Herramientas

Databricks

Kafka

Git

Docker

Kubernetes

Descripción del empleo

Description

Your role will involve collaboration with cross-functional teams, leveraging cutting‑edge technologies, and ensuring scalable, efficient, and secure data engineering practices.

Description

Your role will involve collaboration with cross-functional teams, leveraging cutting‑edge technologies, and ensuring scalable, efficient, and secure data engineering practices.

Responsibilities

• Provide Technical Leadership: Offer technical leadership to ensure clarity between ongoing projects and facilitate collaboration across teams to solve complex data engineering challenges.
• Build and Maintain Data Pipelines: Design, build, and maintain scalable, efficient, and reliable data pipelines to support data ingestion, transformation, and integration across diverse sources and destinations, using tools such as Kafka, Databricks, and similar toolsets.
• Drive Innovation: Leverage innovative technologies and approaches to modernize and extend core data assets, including SQL-based, NoSQL-based, cloud-based, and real-time streaming data platforms.
• Implement Automated Testing: Design and implement automated unit, integration, and performance testing frameworks to ensure data quality, reliability, and compliance with organizational standards.
• Optimize Data Workflows: Optimize data workflows for performance, cost efficiency, and scalability across large datasets and complex environments.
• Mentor Team Members: Mentor team members in data principles, patterns, processes, and practices to promote best practices and improve team capabilities.
• Draft and Review Documentation: Draft and review architectural diagrams, interface specifications, and other design documents to ensure clear communication of data solutions and technical requirements.

Requirements

• Bachelor’s degree typically in Computer Science, Management Information Systems, Mathematics, Business Analytics or another STEM degree.
• Proven experience working within cross-functional teams and managing complex projects from inception to completion
• 4+ years of professional Data Development experience.
• 3+ years of experience with SQL and NoSQL technologies.
• 3+ years of experience building and maintaining data pipelines and workflows.
• 3+ years of experience developing with Python & PySpark.
• Experience developing within databricks.
• Experience applying object-oriented design patterns and principles.
• Experience with CI/CD pipelines and processes.
• Experience with automated unit, integration, and performance testing.
• Experience with version control software such as Git.
• Full understanding of ETL and Data Warehousing concepts.
• Strong understanding of Agile principles (Scrum).

Preferred Qualifications

• Knowledge of Structured Streaming (Spark, Kafka, EventHub, or similar technologies).
• Experience with GitHub SaaS/GitHub Actions.
• Experience with Service Oriented Architecture.
• Experience with containerization technologies such as Docker and Kubernetes.