BI Engineer: Data Pipelines & Modern Analytics

LIDL

Birmingham

Hybrid

GBP 53,000 - 70,000

Full time

14 days+
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Benefits offered by this job

35 days holiday pro rata
10% in-store discount
Enhanced family leave
Pension scheme
Hybrid working

Job summary

Lidl is seeking a Business Intelligence Engineer to join the Head Office Controlling team on a 23-month fixed-term contract. The role focuses on data integrity, scalable architecture, and actionable insight to support reporting and decision-making.

You will work in a hybrid setup with strong collaboration across departments, modernising legacy processes, and delivering reliable BI solutions using Snowflake, BigQuery, and GCP.

Qualifications

  • Expert-level SQL with complex queries and window functions.
  • Advanced Python for building data pipelines and automation.
  • Experience designing and deploying ETL/ELT pipelines.
  • Knowledge of data governance best practices.
  • Data modeling and BI data preparation.
  • Experience with Snowflake and BigQuery in cloud DWs.

Responsibilities

  • Engineer trusted data layers powering reporting and analysis.
  • Design and implement ETL/ELT pipelines to structure complex data.
  • Automate processes and manipulate data programmatically.
  • Work in GCP environments; migrate legacy VBA/Excel macros where applicable.
  • Own data initiatives from requirements to deployment and monitoring.
  • Communicate with non-technical stakeholders to align on needs.

Skills

SQL expertise
Python
ETL/ELT pipelines
Data governance
Data modeling
Cloud data warehouses

Tools

Snowflake
BigQuery
GCP
VBA/Excel

Job description

Lidl is seeking a Business Intelligence Engineer to join the Head Office Controlling team on a 23-month fixed-term contract. The role focuses on data integrity, scalable architecture, and actionable insight to support reporting and decision-making.

You will work in a hybrid setup with strong collaboration across departments, modernising legacy processes, and delivering reliable BI solutions using Snowflake, BigQuery, and GCP.

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