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Senior Data Engineer

Right balance

Description

Engagement Details

Our client is building a career platform focused on data openness, quantitative evaluation, and self-improvement for employees and recruiters. The platform includes a data augmentation and analytics layer that provides users with a single, comprehensible score representing their "human capital." This score is enriched by proprietary data signals to offer a holistic ranking of professionals in the same role. The company has raised $26M in funding and has a remote global engineering team of 7. They emphasize fast iteration, transparency, and seek individuals with high energy and a bias for action. The tech stack includes Python for data processing on AWS, Node.js with Nest.js for the backend API, and React with Next.js for the frontend.

What's in it for you

  1. Learn and evolve your skills using the latest technology tools in a rapidly growing company.
  2. Learn from experienced engineers who constantly challenge the status quo and innovate.
  3. Enjoy flexible working hours with control over your schedule, apart from daily standups, sprint planning, and retrospective meetings.
  4. Work remotely from anywhere, allowing you to choose your preferred work environment.
  5. Tackle challenging problems, innovate, and make a positive impact on people's lives while enjoying the work.

Required Qualifications

  1. Minimum of 7 years of full-time hands-on software engineering experience.
  2. Upper-intermediate to fluent proficiency in spoken and written English, enabling real-time conversations.
  3. Minimum of 3 years of full-time hands-on Data Engineering experience, including experience in companies with 50+ employees.
  4. Minimum of 4 years of full-time hands-on experience as a DBA, DevOps, or Business Intelligence Analyst.
  5. Minimum of 2 years of full-time hands-on Python experience.
  6. Minimum of 2 years of full-time hands-on AWS experience.
  7. Minimum of 1 year of full-time hands-on experience with Apache Airflow or other scheduling tools.
  8. Experience in architecting data infrastructure.
  9. Experience using big data databases such as Presto DB, Athena AWS, Big Table, or similar.
  10. Experience with Python and Pandas.
  11. Experience in architecting databases, including tables, schemas, indexes, and query optimization.

Nice to Haves

  1. Experience as a DBA.
  2. Experience and interest in developing Neural Networks or Machine Learning models.
  3. Experience with data normalization of scrapped datasets.
  4. Experience in building social platforms.
  5. Bachelor's degree in Computer Science or equivalent demonstrated ability.

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