Securitas IT
Securitas’ vision is to become the Intelligent Protective Services Partner by being client centric, data driven and people focused. Our protective services help make your world a safer place. IT is a key function in enabling the modern and powerful technology needed to fulfil Securitas’ business strategy.
About the role
The Senior Data Platform Lead is a critical senior technical leadership role responsible for owning and evolving the organization's core data platform, driving engineering excellence across Databricks, Fabric and the broader technical data ecosystem. This leader will balance hands-on technical oversight with strategic engagement - acting as the connection between platform engineering, business demand, and strategically important data programmes.
This role suits a seasoned data engineer or architect who has grown into leadership, retains a strong technical grounding, and can credibly engage with both engineers and executive stakeholders.
Securitas Group utilizes a federated operating model, and it is essential that the Data Platform supports this framework while aligning with our strategic objectives.
Key responsibilities
1. Data Platform Ownership & Engineering Leadership
- Own the technical strategy, architecture, and roadmap for the organization's data platform, with Databricks as the primary compute and analytics engine.
- Provide a clear Service Description of the Platform options and expected roles and responsibilities in our Federated Environment.
- Lead platform reliability, performance, and scalability - ensuring SLAs are met and operational risk is minimized.
- Establish and enforce engineering standards, including CI/CD pipelines, infrastructure-as-code, and testing practices all in a Federated Environment
- Oversee cluster configuration, cost management, and resource optimization within Databricks.
- Drive adoption of platform best practices across Delta Lake, Unity Catalog, MLflow, and related components.
2. Demand Management & Stakeholder Engagement
- Create a true Business/Consumer orientated Data Products shopping experience.
- Work with the Enterprise Data Governance team to technically realise data governance and data quality frameworks in the platform.
- Act as the primary technical point of contact for data platform demand, triaging and prioritising requests from business units, analytics teams, and product owners.
- Partner with business stakeholders to translate requirements into platform solutions, balancing speed-of-delivery with architectural integrity & platform roadmap.
3. Strategic Data Program Support
- Serve as a senior technical contributor and platform authority on enterprise data transformation programs (e.g. cloud migration, data product adoption, AI/ML enablement).
- Collaborate with data architects, data product owners, and data governance leads to align platform capabilities with strategic initiatives.
- Provide technical due diligence and risk assessment for new tools, vendors, and integration patterns.
- Contribute to data strategy documentation, business cases, and executive presentations where platform capability is relevant.
4. Integration & Data Movement
- Lead or oversee the design of data integration patterns, including batch ingestion, event streaming, and API-based data movement.
- Ensure robust connectivity between Databricks and upstream/downstream systems (ERP, CRM, SaaS platforms, data warehouses, client portals).
- Evaluate and manage integration tooling (e.g. ADF, dbt, Fivetran, Kafka, or equivalent) in line with platform strategy.
- Define standards for data contracts, schema management, and pipeline observability.
5. Team Leadership & Development
- Directly manage and develop a team of data engineers and platform engineers (4-7 consultants), including performance management, coaching, and professional growth.
- Foster a culture of engineering excellence, continuous improvement, and collaborative problem-solving.
- Manage third-party vendor relationships where applicable.
- Support financial plan up to a 3-year time horizon based on the Platform Strategy & backlog, industry trends and Business needs.
Requirements
Key competencies
- Technical Depth - can engage deeply on platform architecture, code quality, and engineering trade-offs — not just at a conceptual level.
- Strategic Thinking - connects platform decisions to business outcomes; anticipates future needs and plans accordingly.
- Stakeholder Management - communicates clearly with both technical and non-technical audiences; builds trust across the organisation by meaningfully engaging with senior technical and business stakeholders.
- Delivery Focus - prioritises pragmatically, manages complexity, and consistently moves things forward.
- People Leadership - develops talent, builds psychological safety, and gets the best from diverse teams.
- Data Governance Mindset - understands the importance of data quality, cataloguing, access control, and lineage.
Skills & Experience
Essential
- Around 10+ years of experience leading data platform and/or data engineering teams in a complex enterprise environment.
- Deep hands-on expertise with Databricks, including Spark, Delta Lake, Databricks SQL, Workflows, and Unity Catalog.
- Strong understanding of lakehouse architecture, cloud-native data infrastructure (Azure preferred/AWP/ GCP), and modern data stack principles.
- Experience owning a technical platform end-to-end — including reliability, security, cost, and roadmap.
- Track record of working across business and technology stakeholders to manage demand and deliver outcomes.
- Previous experience with leading a team.
- Familiarity with data governance, data cataloguing, and metadata management practices.
- Fluency in English.
Highly Desirable
- Background in data integration - including pipeline design, event streaming (Kafka, Event Hubs), or ETL/ELT tooling (dbt, ADF, Fivetran, or similar).
- Experience contributing to large-scale strategic data programs (e.g. cloud migration, data platform modernisation, AI/ML platform build-out).
- Exposure to data mesh, data product thinking, or domain-oriented data ownership models.
- Familiarity with MLflow, Feature Store, or Databricks Model Serving for ML workloads.
Leadership & Behavioral
- Demonstrates executive presence and the ability to influence without authority.
- Brings clarity and calm to ambiguous, fast-moving environments.
- Is a natural collaborator who builds strong relationships across engineering, architecture, and business functions.
- Has a growth mindset - curious, adaptive, and committed to both personal and team development.
- Reference to our Leadership Framework (checked during recruitment process).
Working conditions
We are currently welcoming applications from candidates based in European countries where our company has an established entity.
This role follows a hybrid working model (with office attendance requirements aligned with local office regulations) and regular travel.
What we offer
At Securitas we believe in doing the right thing and doing it well. For our customers and our employees. Our employees come from all walks of life and bring with them many talents and perspectives. We aim for diverse representation throughout the company, and we are committed to equal pay, safe working conditions, gender balance and an inclusive work environment with a wide range of skills and development opportunities.
If this sounds like the right next step in your professional career, don't hesitate and apply!
