DO|BC - Data Engineer / ETL Developer

Huenei IT Services; Buenos Aires; On-site; ARS 2,000,000 - 4,000,000; Full time

Benefits offered by this job

Continuous training program

Flexible working hours to support work

In-company English classes

Employee referral program

Benefits platform

Job summary

Huenei IT Services is seeking a Data Engineer to join our team in Buenos Aires. You will work on designing and delivering modern data solutions, auditing multi-agent pipelines, and ensuring data quality across Spark workloads.

The role requires strong Python/SQL skills, Spark/PySpark experience, and familiarity with Databricks and Delta Lake. You will collaborate with architects and engineers to produce production-ready solutions and contribute to cloud transformation initiatives.

Qualifications

• Proven experience in Data Engineering or ETL Development.
• Strong hands-on experience with Python and SQL in production environments.
• Experience developing and optimizing solutions using Apache Spark / PySpark.
• Knowledge of Databricks (Asset Bundles experience is a plus).
• Solid experience with Git, Pull Requests, and code review as part of a regular development workflow.
• Familiarity with data platforms and technologies such as Delta Lake, T-SQL, SSIS, and SQL Server Agent.
• Experience working with CI/CD practices; exposure to Azure DevOps is desirable.
• Ability to review, validate, and troubleshoot code written by other developers.
• Strong analytical and problem-solving skills, with the ability to exercise independent technical judgment.
• Experience working with AI-assisted development tools and modern software delivery practices.

Responsibilities

• Operating and auditing the multi-agent system, reviewing execution plans and validating generated code bundles to ensure scalability, performance, and data quality.
• Analyzing and detecting bottlenecks such as data skew, excessive shuffles, inefficient transformations, and incorrect data typing within Spark workloads.
• Designing and executing data parity and reconciliation tests to certify that Databricks outputs fully match legacy source loads in terms of volume, values, and schemas.
• Resolving minor code warnings and technical issues independently while escalating complex events, pattern changes, and semantic inconsistencies to the Architect when required.
• Reviewing and remediating code quality, security, and compliance findings identified through SAST tools, dependency scans, and internal standards before Pull Request submission.
• Managing feature branches and Git workflows, ensuring compliance with development standards, pre-check validations, and code review practices.
• Leading the resolution of rejected tickets, defects, and issues identified during QA and UAT phases.
• Supporting deployment activities, monitoring pipeline performance, and maintaining operational stability during the post-deployment hypercare period until formal handover to support teams.
• Collaborating with architects, engineers, and AI-assisted development tools to deliver approved designs as validated and production-ready solutions.

Skills

Python

SQL

Data engineering

PySpark

Spark

Databricks

Git

CI/CD

Azure DevOps

Tools

Git (PRs)

Databricks

Delta Lake

SSIS

Azure DevOps

Job description

At Huenei, we keep growing and adding talent to our Tribe!

If you're someone who:

• Likes to challenge the status quo
• Thinks outside the box
• Has a curious and agile mindset
• Enjoys creating as part of a team
• Is passionate about digital transformation
• Is eager to grow professionally and continuously learn
• Values a fun and engaging work environment

At Huenei, we take pride in delivering cutting-edge solutions to our clients, and we're committed to innovation and the professional growth of our team. If you're passionate about designing and delivering modern data solutions, solving complex technical challenges, and contributing to large-scale cloud transformation initiatives, this opportunity is for you!

Now, imagine yourself in this position

• Operating and auditing the multi-agent system, reviewing execution plans and validating generated code bundles to ensure scalability, performance, and data quality.
• Analyzing and detecting bottlenecks such as data skew, excessive shuffles, inefficient transformations, and incorrect data typing within Spark workloads.
• Designing and executing data parity and reconciliation tests to certify that Databricks outputs fully match legacy source loads in terms of volume, values, and schemas.
• Resolving minor code warnings and technical issues independently while escalating complex events, pattern changes, and semantic inconsistencies to the Architect when required.
• Reviewing and remediating code quality, security, and compliance findings identified through SAST tools, dependency scans, and internal standards before Pull Request submission.
• Managing feature branches and Git workflows, ensuring compliance with development standards, pre-check validations, and code review practices.
• Leading the resolution of rejected tickets, defects, and issues identified during QA and UAT phases.
• Supporting deployment activities, monitoring pipeline performance, and maintaining operational stability during the post-deployment hypercare period until formal handover to support teams.
• Collaborating with architects, engineers, and AI-assisted development tools to deliver approved designs as validated and production-ready solutions.

If you have ...

• Proven experience in Data Engineering or ETL Development.
• Strong hands-on experience with Python and SQL in production environments.
• Experience developing and optimizing solutions using Apache Spark / PySpark.
• Knowledge of Databricks (Asset Bundles experience is a plus).
• Solid experience with Git, Pull Requests, and code review as part of a regular development workflow.
• Familiarity with data platforms and technologies such as Delta Lake, T-SQL, SSIS, and SQL Server Agent.
• Experience working with CI/CD practices; exposure to Azure DevOps is desirable.
• Ability to review, validate, and troubleshoot code written by other developers.
• Strong analytical and problem-solving skills, with the ability to exercise independent technical judgment.
• Experience working with AI-assisted development tools and modern software delivery practices.

Nice to Have

• Basic knowledge of Alteryx and SSIS.
• Experience with pytest and automated testing frameworks.
• Knowledge of application security and secure coding practices.
• Advanced Git workflow expertise.
• Exposure to Databricks Asset Bundles and deployment automation.

Huenei Benefits

• Continuous training program
• Flexible working hours to support work-life balance
• In-company English classes
• Employee referral program
• Benefits platform