Senior Data Engineer (GCP)

TL;DR

Senior Data Engineer (GCP): Building and optimizing high-scale, secure, automated data processing pipelines on GCP with an accent on cloud compute efficiency, data governance, quality, and consumption. Focus on designing and building production-level pipeline code, solving challenges across data science disciplines like classification and optimization, and ensuring data stability under heavy traffic.

Location: Hybrid in Edinburgh or London, UK

Company

hirify.global is an an award-winning global leader and technology innovator in big data analytics and advertising, helping brands understand and effectively reach their best audiences.

What you will do

• Design, build, monitor, and support large-scale data processing pipelines.
• Support, mentor, and pair with other team members to advance team capabilities.
• Help hirify.global explore and exploit new data streams to support commercial and technical growth.
• Work closely with Product and deliver against fast-paced decisions for customers.

Requirements

• 5+ years of direct experience delivering robust, performant data pipelines within commercial financial footprints.
• Proven experience in architecting, developing, and maintaining Apache Druid and Imply platforms, with a focus on DevOps practices.
• Mastery of building pipelines in GCP, maximizing the use of native and native-supporting technologies (e.g., Apache Airflow).
• Mastery of Python for data and computational tasks, with fluency in data cleansing, validation, and composition techniques.
• Hands-on implementation and architectural familiarity with all forms of data sourcing (e.g., streaming data, relational/non-relational databases, distributed processing like Spark).
• Advanced knowledge of cloud-based services specifically GCP and excellent working understanding of server-side Linux.

Nice to have

• Experience optimizing both code and config in Spark, Hive, or similar tools.
• Practical experience working with relational databases, including advanced operations such as partitioning and indexing.
• Knowledge and experience with tools like AWS Athena or Google BigQuery to solve data-centric problems.
• Understanding and ability to innovate, apply, and optimize complex algorithms and statistical techniques to large data structures.
• Experience with Python Notebooks, such as Jupyter, Zeppelin, or Google Datalab.

Culture & Benefits

• Work on fantastically high-scale systems processing over 350GB of data an hour and responding to 400,000 decision requests per second.
• Join a growing team with big responsibilities, significant freedom, and ambitious goals, adhering to Lean Development.
• Values centered on being Brave (innovation and growth mindset), loving clients (client obsessed, integrity), being Inclusive (empathetic, diverse, mutual respect), and Solutions driven (action-oriented, agile).
• Opportunity to take ownership and be accountable for outcomes, solving everyday challenges and achieving breakthroughs.