At Valtech, we’re looking for a Senior Spark Data Engineer to join our team. You will be a curious problem solver who thrives at the intersection of technology, creativity, and data, focusing on building and supporting batch and real-time data pipelines. You’ll work within our borderless, global framework that enables seamless collaboration.

What You'll Do

Demonstrate deep knowledge to build and support non-interactive (batch, distributed) and real-time, highly available data pipelines.
Build fault-tolerant, self-healing, adaptive, and highly accurate data computational pipelines.
Provide consultation and lead the implementation of complex programs.
Develop and maintain documentation for all assigned systems and projects.
Tune queries running over billions of rows of data in a distributed query engine.
Perform root cause analysis to identify permanent resolutions to software or business process issues.

What We're Looking For

Proven industry experience in data engineering, analytics, and/or data science projects, or a Bachelors/Masters degree in a quantitative field.
More than 2 years working with strong/expert Spark (PySpark) using Databricks, Jupyter Notebooks, or Colab.
More than 2 years of hands-on data pipeline development and ingest patterns in Azure orchestration tools like Azure Data Factory (ADF) or Airflow.
More than 2 years of experience working with SQL.
More than 2 years of experience with Denormalized Data modeling for big data systems.
Collaborative, proactive, communicative, able to work remotely while remaining engaged as a team member.
Strong analytical and design skills.
Advanced English Level.

Nice to Have

Familiarity with visualization/reporting tools such as Tableau and PowerBI.
Familiarity with semantic/metadata layer tools like Databricks Unity Catalog and Azure Purview.
Proficiency scripting in a UNIX environment.
Proficiency in big data environments and tools such as Spark, Hive, Impala, Pig, etc.
Proficiency with cloud architecture components (AWS, Azure, Google).
Proficiency with data pipeline software like Airflow, Azure Data Factory, or Prefect.
Familiarity with front and back-end web application stacks and frameworks (Javascript, HTML, CSS, React/Vue/AngularJS) and API design (REST/GraphQL).
Experience leading and managing technical data/analytics/machine learning projects.

Technical Stack

Spark (PySpark), Databricks, Jupyter Notebooks, Colab
Azure Data Factory, Airflow, SQL
Tableau, PowerBI
Databricks Unity Catalog, Azure Purview
Hive, Impala, Pig
AWS, Azure, Google Cloud
Javascript, HTML, CSS, React/Vue/AngularJS, REST/GraphQL

Benefits & Compensation

Flexibility, with remote and hybrid work options (country-dependent).
Career advancement, with international mobility and professional development programs.
Learning and development, with access to cutting-edge tools, training and industry experts.

Work Mode

This is a remote position based in Colombia.

We are committed to inclusion and accessibility. If you need reasonable accommodations during the interview process, please either indicate it in your application or let your Talent Partner know.