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Data Engineer

ByteBridge Technologies, IncPlano, TX🇺🇸United StatesPosted 8 Sept 2026

Quick Overview

Seniority
Mid Senior
Work mode
On Site
Location
Plano, TX, United States
Posted
21 hours ago
AWSETLSnowflakeApacheApache SparkData PipelineDatabricksJavaPython

Job Description

Job Title: Data Engineer

Location: Plano, TX – 5 Days Onsite
Job Type: Contract
Work Authorization: W2 Candidates Only
Experience: 12+ Years
Location Requirement: Local/nearby candidates preferred

Job Summary

We are looking for an experienced Data Engineer with 12+ years of experience in designing, developing, and maintaining scalable data solutions. The ideal candidate should have strong hands-on experience with Databricks, Snowflake, Apache Spark, Java, and Python.

The candidate must be comfortable working onsite 5 days per week in Plano, TX and should be local or within a reasonable commuting distance.

Required Skills

  • 12+ years of experience in Data Engineering or related roles.
  • Strong hands-on experience with Databricks.
  • Strong experience with Snowflake and modern cloud data platforms.
  • Excellent knowledge of Apache Spark for large-scale data processing.
  • Strong programming experience with Python and Java.
  • Experience designing and developing scalable data pipelines and ETL/ELT processes.
  • Strong understanding of data processing, transformation, integration, and data quality.
  • Ability to troubleshoot and optimize data pipelines and Spark jobs.
  • Strong analytical and problem-solving skills.

Preferred Skills

  • Experience with Amazon EMR.
  • Experience with AWS cloud services and data engineering solutions.
  • Experience working with distributed data processing and cloud-based data platforms.

Key Responsibilities

  • Design, develop, and maintain scalable data pipelines and data processing solutions.
  • Develop data transformation and integration workflows using Databricks and Spark.
  • Work with Snowflake for data storage, processing, and analytics.
  • Develop and maintain applications and data processing components using Python and Java.
  • Optimize data pipelines and Spark workloads for performance and scalability.
  • Collaborate with data architects, analysts, developers, and business stakeholders.
  • Troubleshoot data pipeline, processing, and integration issues.
  • Implement data quality, validation, and monitoring processes.
  • Contribute to the design and implementation of cloud-based data solutions.
  • Follow best practices for security, performance, scalability, and maintainability.

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