Senior Data Engineer

TL;DR

Senior Data Engineer (Kafka/Spark): Designing, developing, and maintaining data pipelines, and building infrastructure using Terraform with an accent on Kafka, Spark, Flink, and standard computer science concepts. Focus on troubleshooting and resolving data engineering issues, ensuring data availability and accessibility, and staying up-to-date on the latest trends.

Location: On-site in London four days per week, with the flexibility to work remotely one day each week.

Salary: £50,000 - £110,000 a year

Company

hirify.global is the leading marketplace platform for beauty & wellness trusted by millions of consumers and businesses worldwide.

What you will do

• Design, develop, and maintain data pipelines using Kafka and other tools.
• Build and maintain infrastructure using Terraform.
• Troubleshoot and resolve data engineering issues.
• Work with other teams to ensure that data is available and accessible.
• Take part in decisions related to how new projects are undertaken and gather requirements.

Requirements

• Bachelor's degree in Computer Science or a related field.
• 5+ years of experience as a Data Engineer.
• Strong understanding of Kafka, Spark, Flink, and standard computer science concepts.
• Experience with cloud-based infrastructure (AWS, Azure, GCP).
• Excellent communication and problem-solving skills.
• Ability to work independently and as part of a team.

Nice to have

• Experience with relational databases (PostgreSQL).
• Experience with Snowflake.
• Experience with Flink & Spark.
• Experience with NoSQL databases (Redis, ElasticSearch, etc.).
• Experience with high availability systems and event-driven systems.

Culture & Benefits

• Competitive salary and benefits package.
• Opportunity to work on cutting-edge technology.
• Chance to make a real impact on a growing company.
• Work with a team of talented and passionate engineers.

Hiring process

• Informal meeting with Talent Partner (1 hour).
• 1st Stage Interview with Head of Data & Infrastructure (30 minutes).
• 2nd Stage Technical Google Hangout OR onsite with 2 members of the data Engineering team (Up to 2.5 hours).
• Final Stage Google Hangout interview with CTO (1 hour).