Principal Data Engineer

Jobtailor

Arizona

On-site

USD 120,000 - 150,000

Full time

14 days+

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Job summary

Jobtailor is seeking a hands‑on data engineering leader to design, build, and optimize a modern, cloud‑based data platform. You will shape data architecture, mentor engineers, and drive scalable solutions across analytics, product, and business teams.

Responsibilities include developing scalable data pipelines, implementing ETL/ELT with Azure services, and managing Snowflake and ADLS datasets. Strong SQL, data modeling, and cloud cost optimization are essential for success.

Qualifications

  • 8+ years of experience in data engineering, data architecture, or related roles.
  • Strong SQL development and data modeling expertise.
  • Hands-on experience with Snowflake, ADF, ADLS, Azure Functions.
  • Proficient in Python and ETL/ELT design and implementation.
  • Experience designing scalable data integration and analytics on Azure.
  • Knowledge of modern data architecture patterns and best practices.

Responsibilities

  • Design, build, and optimize a modern cloud data platform.
  • Define data architecture standards and lead engineering efforts.
  • Mentor team members and drive scalable data solutions.
  • Develop and maintain scalable data pipelines for reporting and analytics.
  • Build ETL/ELT solutions using cloud technologies.
  • Implement data integration using Azure services (ADF, ADLS, Functions).
  • Manage datasets in Snowflake and ADLS environments.
  • Lead architecture initiatives including modeling, ingestion, and storage.
  • Drive performance tuning and cloud cost optimization.
  • Establish engineering best practices and code reviews.
  • Collaborate with analytics, product, and business stakeholders.

Skills

Snowflake (SQL)
Azure Data Factory (ADF)
Azure Data Lake Storage (ADLS)
Azure Functions
Python
SQL development
Data modeling
ETL/ELT design & implementation
Cloud cost optimization

Tools

Snowflake (SQL)
Azure Data Factory (ADF)
Azure Data Lake Storage (ADLS)
Azure Functions

Job description

Responsibilities
  • Serve as a hands‑on technical leader responsible for designing, building, and optimizing Cambridge's modern data platform.
  • Help define data architecture standards, lead engineering efforts, mentor team members, and drive scalable data solutions.
  • Design, develop, and maintain scalable data pipelines supporting enterprise reporting, analytics, and business applications.
  • Build and optimize ETL/ELT solutions using modern cloud‑based technologies.
  • Design and implement data integration solutions utilizing Azure Data Factory (ADF), Azure Functions, and other Azure services.
  • Develop and maintain datasets within Snowflake and Azure Data Lake Storage (ADLS) environments.
  • Lead data platform architecture initiatives, including data modeling, ingestion, transformation, storage, and consumption patterns.
  • Drive performance tuning and cost optimization efforts across cloud data platforms and processing workloads.
  • Design secure, reliable data movement solutions using batch and streaming integration patterns.
  • Establish engineering best practices, code reviews, and architectural standards.
  • Mentor data engineers and provide technical leadership across projects.
  • Partner with analytics, product, and business stakeholders to deliver scalable, high‑quality data solutions.
Requirements
  • 8+ years of experience in data engineering, data architecture, or related technical roles.
  • Strong hands‑on experience with:
    • Snowflake (SQL)
    • Azure Data Factory (ADF)
    • Azure Data Lake Storage (ADLS)
    • Azure Functions
    • Data Pipeline Development
    • ETL / ELT Design and Implementation
    • Performance Tuning
    • Cloud Cost Optimization
    • Python
  • Strong SQL development and data modeling expertise.
  • Experience designing scalable data integration and analytics solutions in Azure.
  • Knowledge of modern data architecture patterns and best practices.
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