Senior Data Engineer - Scalable GCP Pipelines

Blis; Greater London; Hybrid; GBP 90,000 - 120,000; Full time

Job summary

Blis is seeking a Senior Data Engineer to design, build and operate large-scale data pipelines on GCP. The role blends software, cloud and data processing engineering, focusing on production-grade pipelines, data governance and scalable architectures.

You will work in a hybrid London-based team, collaborating with product and analytics to enable real-time and batch data workloads, using Python and Airflow to automate workflows and ensure data quality.

Qualifications

• 5+ years direct experience delivering robust data pipelines with SLA and budgets.
• Architecting, developing, maintaining Apache Druid and Imply platforms; DevOps focus.
• Building pipelines in GCP maximizing native tools (Airflow).
• Fluent Python for data tasks; cleansing, validation, composition.
• Hands-on with streaming, relational/non-relational databases, Spark.
• Proficient with Python data libraries (pandas, numpy, scikit-learn).
• Cloud know-how, especially GCP; Linux server-side mastery.
• Documentation, testing, and assurance of solutions.

Responsibilities

• Design, build, monitor, and support large scale data processing pipelines.
• Support, mentor, and pair with team members to increase capabilities.
• Explore and exploit new data streams to support growth.
• Collaborate with Product; deliver fast-paced decisions to delight customers.

Skills

Python

Data pipelines

GCP

Airflow

Spark

SQL/Databases

Linux

Data governance

Tools

Apache Druid

Imply

Google BigQuery

AWS Athena

Job description

Blis is seeking a Senior Data Engineer to design, build and operate large-scale data pipelines on GCP. The role blends software, cloud and data processing engineering, focusing on production-grade pipelines, data governance and scalable architectures.

You will work in a hybrid London-based team, collaborating with product and analytics to enable real-time and batch data workloads, using Python and Airflow to automate workflows and ensure data quality.