Defence Data Engineer: Snowflake & Databricks, Hybrid

CPS Group (UK) Limited

Blandford Forum

Hybrid

GBP 68,000 - 83,000

Full time

2 days ago
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Job summary

CPS Group (UK) Limited is seeking an experienced Data Engineer for a hybrid role in Blandford Forum. 3 days onsite with 2/3 days onsite, with travel and accommodation expenses paid if required, and a salary up to £75,000 depending on experience.

You will design robust data pipelines, manage data quality and governance, and collaborate with stakeholders on mission-critical data solutions. The role requires strong SQL and Python skills, experience with Snowflake and Databricks, and familiarity

Qualifications

  • Experience in a Data Engineer role.
  • Knowledge of Snowflake and Databricks is essential.
  • SQL and Python skills with data-pipeline experience.
  • Knowledge of data modelling, integration, quality and governance.
  • AWS preferred.
  • Experience in complex or secure environments.

Responsibilities

  • Design, develop and maintain ETL frameworks and data pipelines.
  • Ingest, transform, cleanse and validate large-scale datasets.
  • Develop data models to support analytics, reporting and decision-making.
  • Manage data quality, governance, security and compliance standards.
  • Monitor and optimise data workflows for performance, reliability and cost.
  • Collaborate with stakeholders to understand requirements and improve data solutions.

Skills

SQL
Python
ETL
Data pipelines
Data modelling
Data governance
Security & compliance

Tools

Snowflake
Databricks
AWS

Job description

CPS Group (UK) Limited is seeking an experienced Data Engineer for a hybrid role in Blandford Forum. 3 days onsite with 2/3 days onsite, with travel and accommodation expenses paid if required, and a salary up to £75,000 depending on experience.

You will design robust data pipelines, manage data quality and governance, and collaborate with stakeholders on mission-critical data solutions. The role requires strong SQL and Python skills, experience with Snowflake and Databricks, and familiarity

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