Lead Data Engineer

Location: Hybrid - minimum of 1 day pw in London

Salary: From £70,000 + 10% discretionary bonus

Level: Lead-level, with ownership of data engineering standards, platform architecture, and a small team

We are looking for a Lead Data Engineer to join our SMG Platform team. In this role, you will lead the design, delivery and evolution of scalable, secure, and high-performing data platforms, combining hands‑on engineering with architectural oversight. You’ll shape how data is integrated, governed and activated across the business, enabling analytics, AI and commercial decision‑making at scale.

If you love variety, thrive in a fast‑paced environment, and embrace change with energy, this could be your right role.

At SMG, we hire for the future, which is fast‑moving and changing shape
. Do you have the potential to help shape our business? We’re looking for brilliant, diverse talent who want to grow with us—people who are curious, ambitious, and eager to learn, whether as specialists or across teams.

Our culture is everything. If you’re someone who stays honest, stays hungry, stays foolish, and has fun, you’ll feel right at home here.

We value those who take ownership of their growth and bring fresh perspectives. That’s why we’re committed to equity, inclusion, and building a place where everyone feels empowered to grow
. At SMG, it’s not just about filling a role but building the future together.

• 10% discretionary bonus
• £1,800 yearly wellbeing fund (on top of your salary!)
• Free Headspace subscription
• £500 yearly “Learning Fund” for learning
• 4 extra Wellbeing Days off per year
• 4pm finishes every Friday
• Flexible and hybrid working

Explore all our benefits here

We move fast, adapt quickly, and like to challenge each other. We’re looking for people who enjoy the buzz of change, the satisfaction of building something better, and the joy of working with a close‑knit, values‑driven team
.

This isn’t for everyone, but if you thrive in this environment, we’d love to meet you!

You’ll bring:

• Strong experience in data engineering or data platform roles with hands‑on expertise in SQL, Python and distributed processing frameworks (e.g. Spark)
• Proven track record designing and operating modern cloud data platforms (e.g. Snowflake, Databricks)
• Deep understanding of cloud environments (Azure/AWS) and associated data services
• Experience implementing secure data practices including access control, encryption, and audit logging
• Knowledge of CI/CD, infrastructure‑as‑code (e.g. Terraform), and Git‑based workflows
• Experience building high‑quality, well‑documented data products for analytics and BI use cases
• Strong stakeholder communication skills, with the ability to translate technical concepts into business value
• Experience mentoring or leading engineers while remaining hands‑on with development

Some additional nice to haves:

• Experience with orchestration tools (Airflow, Azure Data Factory) and dbt
• Familiarity with BI tooling such as Power BI
• Exposure to MLOps, feature stores, or AI/ML data platforms
• Knowledge of GDPR and secure data sharing practices
• Experience with in retail, commerce media or AdTech environments

Don’t meet every single requirement? We still want to hear from you. If you believe you’d thrive in this role, your unique perspective might be just what we’re looking for.

Your days will be dynamic. You might find yourself:

• Designing and building scalable data pipelines across ingestion, transformation and delivery layers
• Defining and implementing reusable data engineering patterns and best practices
• Optimising performance and cost across cloud‑based data platforms
• Establishing CI/CD, testing frameworks, and data quality standards
• Leading and mentoring a team of Data Engineers while contributing hands‑on to complex builds
• Collaborating with BI, Analytics, Product and AI teams to deliver reliable data products
• Driving data platform observability, monitoring, lineage and SLA reporting
• Leading incident response and improving platform reliability through post‑incident reviews
• Supporting secure data sharing, governance, and compliance with internal and client requirements
• Enabling analytics and AI teams with clean, well‑structured and governed datasets

Stay honest. Stay hungry. Stay foolish. Have fun.

Explore what that means to us here

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