Senior Data Engineer: Build Scalable AI Data Solutions

SunnyData

Mexico

On-site

PHP 7,348,438 - 11,022,658

Full time

14 days+

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Job summary

SunnyData is seeking a Senior Data Engineer to help customers on their data journey, building end-to-end data solutions for AI, ML, and BI. You will collaborate with internal teams and clients to design, deploy, and operationalize data pipelines and governance frameworks.

The role emphasizes strong communication, leadership, and the ability to manage multiple accounts while delivering robust data solutions across Spark, Hadoop, Kafka, and SQL environments.

Qualifications

  • Bachelor’s degree in CS or engineering related field.
  • 5+ years of experience in data engineering and data product development.
  • Experience with data engineering tech (Spark, Hadoop, Kafka).
  • Proficient in end-to-end data analytics workflows.
  • Demonstrated problem solving and debugging skills.
  • Strong English verbal and written communication.

Responsibilities

  • Support new and existing customers in their data engineering needs.
  • Guide customers to make best technical decisions.
  • Work across multiple customer accounts to track progress.
  • Design, build and operationalize complex data solutions and data cleansing.
  • Analyze data sources and assess value for analytics.
  • Ensure data governance, security and quality.

Skills

Leadership
Problem solving
Time management
English communication

Education

Bachelor’s Degree in Computer Science or Engineering related field

Tools

Apache Spark
Hadoop
Kafka
pandas
scikit-learn
SQL
OLTP/OLAP/DSS
Databricks

Job description

SunnyData is seeking a Senior Data Engineer to help customers on their data journey, building end-to-end data solutions for AI, ML, and BI. You will collaborate with internal teams and clients to design, deploy, and operationalize data pipelines and governance frameworks.

The role emphasizes strong communication, leadership, and the ability to manage multiple accounts while delivering robust data solutions across Spark, Hadoop, Kafka, and SQL environments.

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