Mid Data Engineer – Python Spark

At TeamStation AI, we are on a mission to bring together the brightest minds to solve tomorrow’s toughest technology challenges. Our work is about more than just AI—it’s about building the future through collaboration and innovation. We believe that the key to solving the world’s most complex problems lies in aligning diverse talents and perspectives. Our AI-powered platform enables cutting-edge scientific and technical teams to work smarter, faster, and together. By joining us, you’ll help unlock new technological breakthroughs and drive innovation where it matters most.

Join the Mission at TeamStation AI!

Where do we come from? We are seeking visionaries, innovators, and problem solvers who thrive in fast-paced, collaborative environments. If you’re passionate about AI, technology, and solving critical challenges, we want to hear from you. Come be part of a team where your ideas can drive the future.

Location: Latin America Remote

Who We Are

TeamStation AI builds high performing engineering teams across Latin America.

This role supports a TeamStation AI partner in out of home advertising technology. They run a real time operating system for modern media. The platform lives and dies by data quality, data speed, and trust in the numbers. When the data is late or wrong, everything downstream gets noisy.

What You Will Do

1. Build and improve batch and streaming data pipelines with guidance from senior engineers
2. Develop Spark jobs that ingest, transform, and deliver reliable datasets for analytics and AI workloads
3. Implement monitoring and basic data quality checks so issues are detected early and fixed fast
4. Model data for reporting and downstream use in a warehouse, with clear ownership of tables and logic
5. Work inside a cloud data stack and follow solid engineering practices for testing, reviews, and documentation
6. Collaborate with data scientists, analysts, and product teams to turn requirements into clean datasets

Tech Stack and Tools

Data processing

• Apache Spark
• Databricks

Orchestration

• Apache Airflow

Cloud platform

• Amazon Web Services
• Amazon S3
• AWS Glue
• Amazon EMR
• Amazon Kinesis

Warehousing

• Snowflake
• Amazon Redshift

Languages and version control

• Python
• Git

Infrastructure as code

• Terraform

Requirements

1. Four to six years of professional experience in data engineering or a closely related role
2. Strong Python skills for data processing and pipeline development
3. Strong SQL skills for analysis, transformations, and performance optimization
4. Hands on experience building pipelines with Apache Spark and Databricks
5. Experience using orchestration tools like Apache Airflow
6. Working knowledge of dimensional modeling and warehouse design
7. Experience working with AWS data services such as S3, Glue, EMR, and Kinesis
8. Comfortable with code reviews, pull requests, and clean collaboration in Git
9. Fluent English with clear written communication

Nice to Have

1. Experience with Terraform or similar infrastructure as code tools
2. Experience with real time streaming patterns and event driven pipelines
3. Experience working with geospatial datasets or large location based data

What Is In It For You

1. Competitive compensation aligned with experience and impact
2. Fully remote work across Latin America
3. Career growth with mentorship and real ownership over production pipelines
4. Work that directly supports AI systems and real world business decisions

P.S. If you like turning messy data into something people can trust, you will fit in.