Renmoney08.02.26
AI SCORE 8.5

Middle+/​Senior Data Engineer - Cloud DWH Development

$90K–$120K/year

About the Role

We are seeking a talented Middle+/Senior Data Engineer - Cloud DWH Development to join our dynamic team. As a Data Engineer, you will play a crucial role in developing a cloud Data Warehouse (DWH) on AWS, focusing on building and maintaining reliable ETL/ELT pipelines. This is a fantastic opportunity to work remotely and make a significant impact on our data architecture.

What You'll Do

  • Design and implement ETL/ELT pipelines using AWS services such as S3 and Redshift.
  • Utilize Airflow for orchestrating data workflows and ensure data quality improvements.
  • Collaborate with analytics and product teams to enhance data-driven decision-making.
  • Develop and maintain DBT models, tests, and documentation within a Git workflow.
  • Leverage Python for building efficient data pipelines and data processing tasks.
  • Apply knowledge of data modeling approaches and DWH architecture, specifically Data Vault 2.0.
  • Participate in code reviews and contribute to a collaborative team environment.
  • Engage in continuous improvement of data processes and architecture.

Requirements

  • Strong SQL skills, particularly with window functions and optimization for analytical workloads.
  • Proven experience with AWS, specifically S3 and Redshift or other cloud data warehouses.
  • Hands-on experience in building ETL/ELT pipelines and orchestrating them using Airflow.
  • Familiarity with DBT for data modeling and documentation.
  • Proficient in Python for data pipeline development.
  • Understanding of data modeling techniques and DWH architecture.
  • Experience with Git workflows including code reviews and pull requests.
  • Fluency in English at a B2 level or higher.

Nice to Have

  • Experience with CI/CD setups for data projects.
  • Familiarity with streaming data sources like Kafka or Kinesis.
  • Experience with BI tools such as Looker, Power BI, or Tableau.

What We Offer

  • Remote work from anywhere in the world.
  • Performance bonuses, paid vacations, and personal development plans.
  • Transparent processes with minimal documentation requirements.
  • Fast deployment cycles and minimal approvals to see your work's impact quickly.
  • Influence on DWH architecture and the opportunity to propose ideas.
  • A diverse and inclusive team where all voices are valued.
  • Professional growth opportunities and regular feedback sessions.
Language Requirements
EnglishB2
BasicIntermediateAdvancedNative
Why This Job8.5 of 10

This role offers a unique opportunity for a Middle+/Senior Data Engineer to work remotely while developing impactful cloud DWH solutions. With competitive salary and benefits, it's an attractive position for data professionals.

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

Who Will Succeed Here

Proficient in SQL and experienced with AWS services such as S3 and Redshift, demonstrating the ability to design and optimize data models and ETL/ELT pipelines that handle large datasets efficiently.

Self-motivated and comfortable working in a fully remote environment, with strong time management skills to balance multiple projects while delivering high-quality results on tight deadlines.

Hands-on experience with orchestration tools like Airflow and data transformation frameworks like dbt, showcasing a proactive approach to automating workflows and improving data processing efficiency.

Learning Resources

SQL for Data Sciencecourse

Career Path

Middle+/Senior Data Engineer - Cloud DWH Development(Now)Lead Data Engineer(1-2 years)Data Engineering Manager(3-5 years)

Market Overview

Market Size 2024
$10.5B
Annual Growth
12.3%
AI Adoption
45%
Investment
+150%
Labour Demand
+25%
Avg Salary
$120K

Skills & Requirements

Required
SQLAWSS3
Growing in Demand
Apache SparkData WarehousingMachine Learning
Declining
Traditional ETL ToolsHadoop

Domain Trends

Rise of Cloud Data Warehousing
The cloud data warehousing market is expected to grow by 20% annually as businesses shift from on-premises solutions to cloud-based architectures.
Increased Demand for Real-Time Data Processing
Over 60% of organizations are prioritizing real-time data processing capabilities, pushing the need for technologies like Apache Kafka and Airflow.
Integration of AI in Data Engineering
By 2025, 50% of data engineering tasks will be automated through AI, leading to a significant shift in skill requirements towards AI-driven data solutions.

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