Data Engineering Lead

Steadman Brown; Greater London; Hybrid; GBP 90,000 - 130,000; Full time

Job summary

Steadman Brown is seeking a Data Engineering Lead to drive end-to-end data architectures for enterprise-scale transformations. You will collaborate with clients to translate business challenges into data strategies and design modern platforms with Databricks at the core, delivering hands-on implementation and go-live support.

You will lead data workshops, mentor engineers, and partner with pre-sales on proposals.

Qualifications

• Extensive experience designing end-to-end data architectures in enterprise settings.
• Hands-on experience with modern data platforms and tools.
• Strong data engineering skills including building pipelines and data models.

Responsibilities

• Define target-state data architectures that connect systems and processes to business goals.
• Design scalable data platforms with Databricks as a core technology.
• Govern data architecture across projects to ensure consistency and quality.
• Lead hands-on data delivery, building and troubleshooting pipelines with engineering teams.
• Engage with clients and senior stakeholders to shape data strategies.

Skills

Databricks

Snowflake

dbt

SQL

Python

PySpark

Terraform

IaC

CI/CD

AWS

Azure

Git

API design

Salesforce

Job description

Steadman Brown are currently working with one of the UK's leading boutique Salesforce Partners, who have established themselves as a key player in delivering enterprise transformations at scale.

They are now seeking a Data Engineering Lead to work across the full project lifecycle, from pre-sales and client advisory through to architecture, hands‑on delivery and go-live. You'll work closely with clients to understand their business challenges, define data strategies and design data platforms, with Databricks playing a key role within the technology landscape.

Key Responsibilities:

• Define target‑state data architectures that connect systems, data and processes to wider business objectives.
• Design scalable, modern data platforms with Databricks as a key technology within the wider data architecture.
• Govern data architecture across multiple projects, ensuring solutions are consistent and fit for purpose.
• Take a hands‑on approach to delivery, building, configuring and troubleshooting data pipelines and platforms alongside engineering teams.
• Engage directly with clients and senior stakeholders to understand business challenges and shape appropriate data strategies.
• Lead data‑focused workshops, bringing together technical and business stakeholders to define data strategy, architecture and delivery approaches.
• Act as a trusted advisor, helping clients understand how modern data platforms can support their wider digital transformation.
• Support pre‑sales activities including proposals, scoping, technical discovery, prototypes and solution development.
• Stay involved throughout the full project lifecycle, providing continuity from initial client engagement through to delivery and go-live.
• Help develop repeatable data offerings and capabilities aligned to real client and business challenges.
• Provide technical leadership, mentoring and guidance to consultants and engineers across the wider business.
• Help shape the growth and direction of the Data practice, including capability development, hiring and delivery standards.

Experience & Qualifications:

• Extensive experience designing and delivering end‑to‑end data architectures within enterprise environments.
• Strong hands‑on experience with Databricks, ideally alongside modern data platforms such as Snowflake, Microsoft Fabric, dbt or equivalent technologies.
• Hands‑on experience with data engineering tools and technologies including SQL, Python/PySpark, Terraform/IaC and CI/CD pipelines.
• Strong experience across cloud platforms, ideally AWS and/or Azure.
• Good understanding of modern DevOps practices, including Git, CI/CD and Infrastructure as Code.
• Experience designing APIs and integrations and understanding how data platforms connect into wider enterprise technology landscapes.
• Experience working with Salesforce or other CRM platforms within an enterprise data environment would be beneficial.
• Proven experience working directly with clients and senior stakeholders in a consulting or advisory capacity.
• Experience leading data‑focused workshops, technical discovery sessions and architecture engagements.
• Strong commercial awareness with experience supporting pre‑sales, proposals, scoping or solution development.
• Proven leadership experience or clear leadership potential, with the ability to mentor and develop data engineers and consultants.
• Experience working across the full project lifecycle, from discovery and architecture through to implementation and go‑live.