Software Tech Lead - Data & AI

About Selfridges

Here at Selfridges our customers are at the heart of everything we do, and we want to be known for delivering the best, most extraordinary experiences that keep our customers coming back. We are on a journey to build flexible, innovative technology platforms that create inspiring and effortless experiences across all our customer touchpoints.

Our Engineering team plays a central role in shaping these digital experiences, our e-commerce and digital platforms are central to creating innovative, customer-centric experiences. As we grow, we are looking for talented, curious individuals to join us, bring their unique perspectives, and help reimagine our digital platforms to new heights.

This is a hybrid role working from home and our offices in either London or Leicester.

A bit about the role

We’re looking for a Tech Lead to help evolve Selfridges’ Enterprise Data Platform (EDP), the foundation that powers insights, personalisation, and data-driven decision-making across the business.

In this role, you’ll be a leader in shaping the technical direction for our Snowflake-based data ecosystem while supporting the Architecture function. You’ll work across Python, AWS, and Salesforce Data Cloud, helping to design, build, and optimise the pipelines and integrations that connect our digital, store, and enterprise systems.

Alongside your technical delivery, you’ll mentor and line manage engineers, helping them grow their skills and ensuring best practices are embedded across the team. You’ll collaborate closely with architects, analysts, and product teams to deliver secure, performant, and scalable data solutions that enable world-class experiences for our customers.

Key Responsibilities

Lead and contribute to defining the technical direction and standards of the Enterprise Data Platform in collaboration with architecture and engineering leads
Support the Architecture function in designing scalable data models and integration patterns
Lead by example through hands-on design and development of data pipelines in Python, SQL, and AWS services (Lambda, Glue, Step Functions, S3)
Help evolve and maintain the Snowflake environment, focusing on optimisation, governance, and performance
Collaborate on integrations between Snowflake, Salesforce, and enterprise systems, including future Salesforce Data Cloud enablement
Partner with Power BI and analytics teams to ensure data reliability and accessibility for dashboards, insights, and reporting
Work with DevOps and Platform Engineering to enhance CI/CD, observability, and automation practices for data workloads
Drive a strong focus on data quality, reusability, and performance across all ingestion and transformation layers
Line manage and mentor a team of data engineers, conducting regular 1:1s, supporting development plans, and fostering a collaborative, inclusive engineering culture
Collaborate across squads and domains to align data platform delivery with Selfridges’ wider digital and customer experience strategies

A bit about you

Experienced data engineer or technical lead, ideally with previous line management or mentorship experience
Strong hands-on experience with Snowflake and AWS data services (Lambda, Glue, Step Functions, S3, SNS/SQS)
Proficient in Python and SQL, building reliable and maintainable ETL/ELT pipelines
Solid understanding of data modelling (dimensional, star schema, or modern data mesh concepts)
Experience integrating with Salesforce (CRM, APIs, or Data Cloud)
Familiar with Power BI or similar BI tools for downstream analytics and reporting
Knowledge of CI/CD, infrastructure as code (Terraform or CDK), and modern observability tooling
Skilled communicator and collaborator, able to work effectively with architects, product managers, and cross-functional teams
Passionate about engineering excellence, team development, and delivering data solutions that drive real business impact
Enthusiastic about mentoring and supporting engineers’ growth, with a track record of building high-performing teams

Desirable

Experience with dbt, Airflow, or Dagster
Familiarity with event-driven architectures (EventBridge, Kafka, SNS/SQS)
Exposure to data governance, security, and compliance frameworks
Background in retail, loyalty, or customer data platforms
Experience working with or implementing Salesforce Data Cloud integrations
Awareness of AI/ML data readiness practices, including feature engineering, dataset curation, and model-serving pipelines
Familiarity with Snowflake Cortex, AWS Bedrock, or other cloud-native AI/ML services for data enrichment and automation
Interest in emerging GenAI and LLM use cases for personalisation, recommendation systems, and intelligent automation