Staff Analytics Engineer - Cyber Data Platform

Tesco UK; Digswell; Hybrid; GBP 50,000 - 70,000; Full time

Job summary

A leading company in the retail sector is seeking a Staff Analytics Engineer to enhance cybersecurity through innovative data solutions. You will play a crucial role in developing data lakes and optimizing ETL processes, while also coaching an engineering team. The role offers flexibility with 60% of your time in-office, while supporting diverse needs and inclusive practices.

Qualifications

• Proven leadership in delivering data models and analytics frameworks.
• Strong skills in Python and SQL; experience with cloud platforms.
• Knowledge of CI/CD practices and version control.

Responsibilities

• Design and deliver cyber data lake and warehouse solutions.
• Establish standards for coding and data quality processes.
• Lead automation and deployment of data solutions.

Skills

Python

SQL

Data lake concepts

ETL frameworks

Data quality processes

Cybersecurity principles

Tools

Databricks

Airflow

dbt

Tableau

Job description

As the Staff Analytics Engineer on the Cyber Analytics team, you will be key in designing, developing, and deploying scalable data lake and data warehouse solutions and data models that empower our security users to draw insights, develop reporting capabilities, advanced analytics, machine learning, and GenAI solutions to enhance our security defenses.

You will lead data modeling and architectural decisions, guide technical direction, and mentor the analytics engineering team to deliver high-quality data products.

Work Environment and Flexibility

At Tesco, we believe in the power of spending more face-to-face time together. You can expect to spend 60% of your time in office locations or local sites, with the rest remotely. We support flexible working arrangements to accommodate different life circumstances.

Key Responsibilities

• Design, develop, and deliver cyber data lake and data warehouse solutions, analytics frameworks, and processes for cybersecurity use cases.
• Design, build, and manage ETLs and data quality processes to transform source data into trusted data products, implementing a Data as a Service (DaaS) model.
• Establish standards for high-quality coding, conduct peer reviews, and lead documentation efforts for data models and ETLs.
• Implement and enforce data security standards and ensure compliance with relevant regulations.
• Automate deployment, configuration, and management of data solutions using DevOps practices.

Qualifications and Experience

• Proven leadership in delivering robust data models, analytics frameworks, and providing technical guidance.
• Strong programming skills in Python/PySpark and SQL.
• Experience building data lake and data warehouse solutions on cloud platforms like Databricks on Azure, with a DaaS model.
• Knowledge of data lake and warehouse concepts, architectural patterns, coding standards, version control, and CI/CD practices.
• Experience with ETL/ELT frameworks, orchestration tools like Airflow and dbt.
• Experience with enterprise BI tools such as Tableau for visualization and reporting.
• Familiarity with distributed and stream processing frameworks.
• Ability to guide and develop engineering teams.
• Knowledge of cybersecurity principles and practices.

We are committed to inclusive hiring and support for applicants with diverse needs. If you need assistance with your application, click here for more information. We encourage you to apply even if you do not meet every listed requirement.