Senior Big Data Engineer - AWS & Databricks Expert

SoftServe

Chile

Presencial

CLP 9.000.000 - 14.000.000

Jornada completa

hace 18 horas
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Descripción de la vacante

SoftServe in Chile is seeking an experienced Data Engineer to design and implement scalable data pipelines in AWS, leveraging Spark, Databricks, and modern data tools. You will own end-to-end data workflows, optimize performance and costs, and collaborate with AI, product, and engineering teams.

The role requires 5+ years of experience in Big Data/Data Engineering, strong Python and SQL skills, and hands-on AWS data services expertise.

Formación

  • 5+ years of professional experience in Big Data / Data Engineering.
  • Proficient in Python and SQL; Java a plus.
  • Hands-on experience with Spark, Databricks, and AWS data services.
  • Experience with CI/CD, IaC, and Terraform.
  • Strong English communication skills for cross-team collaboration.

Responsabilidades

  • Design, develop, and maintain scalable batch and distributed data pipelines.
  • Build and optimize data processing solutions focusing on performance and cost efficiency.
  • Collaborate with engineering, AI, and product teams to support analytics and AI use cases.
  • Develop data solutions using Python, SQL, Spark, Databricks and AWS services.
  • Work with PostgreSQL and MySQL for data processing workflows.
  • Develop and maintain workflow orchestration with Airflow and data pipelines.
  • Support CI/CD, IaC, testing, and production support using Terraform and related tools.

Conocimientos

Python
SQL
Big Data / Data Eng
English proficiency

Herramientas

Apache Spark
Databricks
AWS Glue
Amazon Athena
Amazon Aurora
PostgreSQL
MySQL
Apache Airflow
Terraform
Apache Kafka

Descripción del empleo

SoftServe in Chile is seeking an experienced Data Engineer to design and implement scalable data pipelines in AWS, leveraging Spark, Databricks, and modern data tools. You will own end-to-end data workflows, optimize performance and costs, and collaborate with AI, product, and engineering teams.

The role requires 5+ years of experience in Big Data/Data Engineering, strong Python and SQL skills, and hands-on AWS data services expertise.

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