Remote Spark Data Engineer - Scale Analytics & Lakehouse

BairesDev

Jalisco

Remote

MXN 800,000 - 1,300,000

Full time

14 hours ago
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Benefits offered by this job

100% remote
USD or local currency
Hardware provided
Flexible hours
Paid parental leave
Vacations & holidays
Mentorship and growth
Global team

Job summary

BairesDev is a remote-first tech company expanding its global data engineering capabilities. We seek a Spark Data Engineer to design and optimize scalable data pipelines and connect raw data sources with analytical platforms.

You will work on high-performance, cost-efficient systems across our data ecosystem. The role focuses on batch and streaming pipelines, data modeling, and collaboration with engineering teams to ensure reliability and data quality.

Qualifications

  • 5+ years of experience in Data Engineering or Software Engineering.
  • Proven expertise building large-scale data pipelines using Apache Spark.
  • Hands-on experience with analytics and lakehouse solutions on Databricks.
  • Strong data modeling, transformation, and processing at scale.
  • Advanced proficiency in English.

Responsibilities

  • Build and maintain scalable batch and streaming data pipelines.
  • Optimize pipelines for performance and cost.
  • Develop analytics and lakehouse solutions at scale.
  • Implement robust data modeling and transformations.
  • Collaborate with engineering teams to ensure data quality and reliability.

Skills

Spark
Databricks
Data modeling
Big data pipelines
English fluency

Education

Bachelor's degree in Computer Science or related field

Tools

Databricks Platform

Job description

BairesDev is a remote-first tech company expanding its global data engineering capabilities. We seek a Spark Data Engineer to design and optimize scalable data pipelines and connect raw data sources with analytical platforms.

You will work on high-performance, cost-efficient systems across our data ecosystem. The role focuses on batch and streaming pipelines, data modeling, and collaboration with engineering teams to ensure reliability and data quality.

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