Data Engineer

Ascendum Solutions; Argentina; Presencial; ARS 1.800.000 - 3.000.000; Jornada completa

Descripción de la vacante

Ascendum Solutions is seeking an experienced Data Engineer to collaborate with cross-functional teams, building scalable data pipelines and modern data platforms using PySpark, SQL/NoSQL, and Databricks.

You will own end-to-end data solutions, implement automated testing, and mentor teammates while aligning with Agile practices. Experience with Docker/Kubernetes and CI/CD is preferred, in a fast-paced environment.

Formación

• Bachelor’s degree in a STEM field.
• 4+ years of professional Data Development experience.
• 3+ years of experience with SQL and NoSQL technologies.
• 3+ years building and maintaining data pipelines and workflows.
• 3+ years developing with Python & PySpark.
• Experience developing within Databricks.
• Experience with CI/CD pipelines and Git.
• Experience with automated unit, integration, and performance testing.
• Understanding of ETL and Data Warehousing concepts.
• Strong understanding of Agile principles (Scrum).

Responsabilidades

• Take ownership of systems, processes, and the tech stack while driving features to completion through all phases of the SDLC.
• Provide Technical Leadership to ensure cross-team clarity and collaboration.
• Build, design, and maintain scalable data pipelines using tools like Kafka and Databricks.
• Drive innovation to modernize core data assets and real-time platforms.
• Implement automated testing frameworks for data quality and compliance.
• Optimize data workflows for performance, cost, and scalability.
• Mentor team members on data principles and best practices.
• Draft and review architectural diagrams and interface specifications.

Conocimientos

Python

PySpark

SQL

NoSQL

Data pipelines

Kafka

Databricks

CI/CD

Git

ETL

Data warehousing

Agile Scrum

Educación

Bachelor’s degree in CS/STEM

Herramientas

Docker

Kubernetes

Descripción del empleo

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

Responsibilities

Take ownership of systems, processes, and the tech stack while driving features to completion through all phases of the entire SDLC. This includes internal and external facing applications as well as process improvement activities:

• 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.