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Remote Senior Data Engineer

Remote: 
Full Remote
Contract: 
Experience: 
Senior (5-10 years)
Work from: 

Offer summary

Qualifications:

Minimum 8 years in data engineering, Proficient in Python and SQL, Experience with SQL query profiling, Familiarity with AWS and Kubernetes preferred, Bachelor's degree in related field preferred.

Key responsabilities:

  • Design scalable data pipelines and systems
  • Implement cloud-native infrastructure on AWS
  • Develop a comprehensive SQL intelligence framework
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2 - 10 Employees
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Job description

Job Overview

We are on the lookout for an enthusiastic and skilled Senior Data Engineer to join our innovative team remotely. This role presents an exciting opportunity for individuals who thrive in solving complex problems and are eager to go beyond conventional data engineering practices. In this position, you will play a pivotal role in optimizing our AI capabilities, constructing high-performance data systems, and seamlessly integrating advanced AI into the workflows of data teams on a global scale.

Key Responsibilities

  • Design and construct robust data pipelines capable of scaling to support over 100,000 jobs and manage petabyte-scale data on a daily basis.
  • Architect and implement cloud-native data infrastructure on AWS, leveraging Kubernetes and Airflow for optimal resource allocation and system deployment.
  • Develop a comprehensive SQL intelligence framework that includes query optimization, dynamic pipeline creation, and data lineage tracking using your expertise in SQL profiling and parsing.

Required Skills

  • Over 8 years of experience in data engineering, primarily focused on the development of scalable data systems.
  • Proficient in Python and SQL, demonstrating strong technical skills.
  • In-depth experience with SQL query profiling, optimization, and performance tuning, ideally with Snowflake.
  • Solid understanding of SQL Abstract Syntax Tree (AST) and experience with SQL parsers (e.g., sqlglot) for generating column-level lineage and dynamic ETLs.
  • Experience in building data pipelines utilizing Airflow or dbt.
  • (Optional) Familiarity with cloud platforms, particularly AWS, and knowledge of Kubernetes (K8s) for containerized deployments.

Qualifications

  • A minimum of 8 years of experience in data engineering, with a strong emphasis on scalable data infrastructure.
  • A Bachelor's degree in Computer Science, Engineering, or a related discipline is preferred.

Career Growth Opportunities

This role is a gateway into the dynamic field of AI-enhanced data engineering, providing invaluable exposure to avant-garde technologies and the implementation of generative AI applications. Our commitment to your professional development is highlighted through extensive learning resources and opportunities tailored to elevate your career.

Company Culture And Values

Join a collaborative and stimulating work environment where creativity and innovation are at the core of our operations. We pride ourselves on fostering a diverse and inclusive workplace that champions teamwork and the continuous pursuit of excellence.

Networking And Professional Opportunities

As a member of our team, you will have the chance to contribute to several high-impact projects and expand your professional network within the tech community, enhancing your visibility and career trajectory.

Compensation And Benefits

  • Competitive Salary Range: \(60,000 - \)120,000, influenced by your expertise, geographic location, interview performance, and role fit.
  • Equity options ranging from 0.0% to 0.4%.
  • Opportunities for professional growth through continuous learning and development programs.
  • A dynamic and inspiring work environment filled with talented peers committed to making an impact.

If you are eager to take your data engineering skills to the next level and make a meaningful difference in the world of data, we encourage you to apply and join us in building something extraordinary.

Employment Type: Full-Time

Required profile

Experience

Level of experience: Senior (5-10 years)
Industry :
Human Resources, Staffing & Recruiting
Spoken language(s):
English
Check out the description to know which languages are mandatory.

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