Talantix.io
Areli•11.03.26
AI SCORE 8.5

Remote Data Engineer - Azure & ETL Specialist

$90K–$120K/year
RemoteData Engineering
Azure PaaS•ETL•SQL•Python•C•Data Modeling•Microsoft SQL Server•BigQuery•Airflow

About the Role

We are seeking a talented Remote Data Engineer to join our dynamic team. In this role, you will leverage your expertise in data engineering to build robust data pipelines and support our data-driven initiatives. As a Remote Data Engineer, you will work with cutting-edge technologies and contribute to projects that have a significant impact on our operations.

What You'll Do

  • Design and implement scalable data pipelines using Azure PaaS and ETL tools.
  • Develop and maintain data models and schemas in Microsoft SQL Server and BigQuery.
  • Collaborate with cross-functional teams to gather requirements and deliver data solutions.
  • Ensure data quality and integrity through rigorous testing and validation processes.
  • Utilize Python and C# for data manipulation and transformation tasks.
  • Document processes and provide technical support to stakeholders.
  • Stay updated with industry trends and best practices in data engineering and cybersecurity.

Requirements

  • 2-5 years of experience as a Data Engineer or in a similar role.
  • Proficiency in SQL and experience with Microsoft SQL Server.
  • Hands-on experience with Azure PaaS and ETL development.
  • Strong programming skills in Python and C#.
  • Familiarity with data modeling and data pipeline architecture.
  • Knowledge of cybersecurity principles, specifically NIST SP 800-53.
  • Excellent communication skills and ability to work in an Agile environment.

Nice to Have

  • Experience with AWS and ELT processes.
  • Familiarity with Airflow for workflow management.
  • Knowledge of Geographic Information Systems (GIS).

What We Offer

  • Competitive salary ranging from $90,000 to $120,000 per year.
  • Flexible remote work environment.
  • Opportunities for professional development and training.
  • Equal opportunity employer committed to diversity and inclusion.
  • Access to the latest tools and technologies in data engineering.
Why This Job8.5 of 10

This Remote Data Engineer position offers a competitive salary and the chance to work with cutting-edge technologies in a flexible environment.

Salary Range
Required
0/1
Optional
0/1
Bonus
0/1

Who Will Succeed Here

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Proficient in Azure PaaS and ETL processes, with hands-on experience in building data pipelines using tools like Azure Data Factory and Apache Airflow to ensure efficient data flow and transformation.

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Self-motivated and disciplined, thriving in a remote work environment where independent problem-solving and proactive communication are essential to collaborating with cross-functional teams.

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A data-driven mindset with strong SQL skills for data modeling and querying, complemented by proficiency in Python for developing data processing scripts and a solid understanding of Microsoft SQL Server and BigQuery.

Learning Resources

→Azure Data Engineering on Microsoft Azurecourse
→Data Engineering with Python and Airflowarticle
→Microsoft Azure Documentationguide

Career Path

Remote Data Engineer - Azure & ETL Specialist(Now)→Data Engineer II / Senior Data Engineer(1-2 years)→Lead Data Engineer or Data Architect(3-5 years)

Market Overview

Market Size 2024
$16.3B
Annual Growth
22.3%
AI Adoption
45%
Investment
+150%
Labour Demand
+30%
Avg Salary
$120K

Skills & Requirements

Required
Azure PaaSETLSQL
Growing in Demand
Azure Data FactoryData LakesMachine Learning with Azure
Declining
On-Premise ETL ToolsTraditional Data Warehousing

Domain Trends

Rise of Serverless Architectures
The adoption of serverless architectures in data engineering is rising, with 60% of organizations planning to implement serverless solutions for data processing by 2025.
Increased Focus on Real-Time Data Processing
Real-time data processing demand is growing, with a projected increase of 40% in companies adopting real-time analytics solutions in the next two years.
Integration of AI and Machine Learning
Integration of AI and machine learning into data engineering processes is expected to grow by 50%, with 70% of data engineers using AI-driven tools by 2025.

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