Lead Data Engineer

Data Idols
Manchester, UK
8 days ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Compensation
ÂŁ75,000.0 - ÂŁ85,000.0
Working hours
Regular working hours

Tech stack

BigQuery Information Engineering Data Systems Cloud Services Google Cloud Data Ingestion Sql Optimization Google Bigquery

Job description

This role sits within a modern data engineering function and focuses on designing robust, scalable architectures for data ingestion and analytics, with BigQuery at the core. You’ll play a key role in setting technical standards, ensuring governance, and shaping best practices across the platform., As the Lead Data Engineer and expert in BigQuery and GCP data services, you’ll guide teams on how to build efficient, compliant, and future-proof solutions. You’ll balance hands-on delivery with mentorship, ensuring solutions meet performance, scalability, and regulatory expectations.

Requirements

This role is well suited to someone who enjoys deep technical problem-solving, influencing standards, and mentoring others in a cloud-native data environment., * Strong experience designing data solutions on Google Cloud Platform

  • Deep hands-on expertise with Google BigQuery, including architecture, optimisation, and advanced SQL
  • Familiarity with CI/CD pipelines
  • Ability to influence technical direction and support other engineers through mentorship

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Good distractions

Talks and stories from around this role — technically off-topic, practically not.

2:30 min

Leveraging BigQuery ML for scalable SQL-based segmentation experiments

Julian Joseph ¡ LIVE

3:03 min

Career evolution in data engineering and AI platforms

Maria Apazoglou ¡ Coffee With Developers

6:10 min

Unlocking free learning credits via Google Cloud Innovators

Asrar Asrar ¡ World Congress 2024

2:37 min

Classifying and anonymizing data during system design

Reto Kaeser ¡ LIVE

1:19 min

The true role and evolution of data engineering

Sandhya Menon Sandhya Menon ¡ World Congress 2026 Europe

3:27 min

Explaining query execution overhead and caching limitations in BigQuery

Adnan Rahic ¡ JS Congress

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