Full-Stack Data Engineer: Big Data & Data Platform Expert

Railway Corp; Mexico; On-site; PHP 5,474,000 - 7,908,000; Full time

Job summary

arenaflex is seeking a Full Stack Data Engineer to join our Information and Investigation group, designing, developing, and implementing cutting-edge data solutions for web-based features and improved customer experiences.

As a key member, you will work with Information Chiefs, Modelers, and Architects to engineer scalable data warehouses, ETL pipelines, and data models using SQL, Python, Java, Hadoop, and Redshift in fast-paced, collaborative teams.

Qualifications

• Solid SQL skills and the ability to write queries to extract insights from large datasets.
• Experience with Big Data technologies such as Hadoop and PySpark.
• Strong programming skills in Python and Java.
• Experience with MPP or distributed database technologies such as Redshift.
• Experience with data integration toolsets and building data pipelines.
• Knowledge of data modeling strategies and data warehousing practices.
• Experience with agile/scrum practices in fast-paced environments.

Responsibilities

• Design and develop data warehouses and data marts for scalable analytics.
• Build and maintain ETL pipelines in Big Data environments and hybrid/on-prem setups.
• Engineer data structures and models in collaboration with information governance teams.
• Collaborate with cross-functional teams to design and implement data solutions for clients.
• Maintain detailed documentation of data architecture and changes.

Skills

SQL

Big Data

Python

Java

Data Integration

Data Modeling

Data Warehousing

Tools

Hadoop

PySpark

Redshift

Job description

arenaflex is seeking a Full Stack Data Engineer to join our Information and Investigation group, designing, developing, and implementing cutting-edge data solutions for web-based features and improved customer experiences.

As a key member, you will work with Information Chiefs, Modelers, and Architects to engineer scalable data warehouses, ETL pipelines, and data models using SQL, Python, Java, Hadoop, and Redshift in fast-paced, collaborative teams.