Senior Data Consultants for the Modern Enterprise Data Stack
Hire senior data consultants with Optiwisers, supplied to enterprises across the UK, France, Switzerland, Germany, Belgium, Netherlands and the Nordics. Nine roles across Snowflake, Databricks, DBT, Power BI, Tableau, data architecture and MDM, mobilised as individual specialists, dedicated teams, managed teams or application management. Boutique precision. Hub-scale capacity.
One Data Consultant Provider. The Full Modern Data Stack.
Data sits alongside SAP inside the Optiwisers Technology Talent Hub. Nine data consultant roles across three buyer outcomes: building the Modern Data Stack (Snowflake, Databricks, DBT, data engineering), delivering analytics and reporting (Power BI, Tableau), and governing data and managing databases (data architects, MDM, DBAs). 60+ specialists across the wider bench, 19+ years of delivery, 7+ countries. Cross-stack reinforcement from SAP, Cloud, AI and Integration where the workload needs it.
Precision Match. Not a CV Pipeline.
We don't send CVs. We identify the data expertise that fits your platform, then integrate it into your team under Optiwisers governance. Boutique precision. Hub-scale capacity. Same senior data bench whether you need a single Snowflake architect, a full Databricks build squad, a BI programme or long-term data platform AMS. Browse by role below, or tell our Data team the outcome you're chasing.
Nearshore Delivery. EU-Compliant. Time-Zone Aligned.
Delivered nearshore from Portugal at 40 to 60% below UK, Swiss and German data integrator rates. EU-compliant, GDPR-aligned, same time-zone as your team. Individual data consultants in one to two weeks. Squads in three to four. Every profile meets our five delivery standards: Validated Profiles, Structured Onboarding, Embedded Governance, Delivery Standards, Reporting & Control. Agility with structure. We move fast. But never blindly. Response within one business day.
Every Data Consultant Role on Our Bench
Nine data consultant roles grouped by three buyer outcomes: building the Modern Data Stack, delivering analytics and reporting, or governing data and managing databases. Each role is delivered nearshore from Portugal as an individual specialist, a dedicated team, a managed team or an application management engagement.
Building the Modern Data Stack
The core of enterprise data work in 2026. Warehouse or lakehouse storage, transformation and ingestion pipelines, and the analytics engineering layer that turns raw data into trusted analytics assets.
Delivering Analytics & Reporting
The layer business users see. BI consultants who turn a working data platform into dashboards, reports and self-service analytics that finance, operations and executives actually use.
Governing Data & Managing Databases
The structural layer. Architects who set the standards, MDM specialists who define the golden record, and DBAs who keep traditional Oracle, SQL Server and PostgreSQL databases running underneath the modern stack.
Four Ways to Engage the Data Bench
Same senior data bench, four commercial structures. Each model was built for a different phase of the data programme lifecycle.
Frequently Asked Questions
Common questions about hiring Optiwisers data consultants.
Optiwisers covers nine data consultant roles across three buyer outcomes. For building the Modern Data Stack: Data engineers, Analytics engineers (DBT), Snowflake consultants and Databricks consultants. For delivering analytics and reporting: Power BI consultants and Tableau consultants. For governing data and managing databases: Data architects, MDM consultants and Database administrators (Oracle, SQL Server, PostgreSQL). SAP MDG lives under our SAP hub. AI engineers, MLOps and LLM engineers live under our AI & ML hub.
Both, and they are covered by dedicated consultant roles on our bench because the two platforms serve different architectural philosophies. Snowflake anchors the warehouse-centric pattern that prioritises standardisation, governed consumption, financial reporting reliability and clean data sharing across business units. Databricks anchors the lakehouse pattern that prioritises flexibility, iterative development and AI/ML workloads that need direct access to raw data. Multi-platform engagements combine one senior consultant per platform in scope with a data architect on top, particularly for enterprises running both patterns for different use cases.
We deliver nearshore to enterprises across the UK, France, Switzerland, Germany, Belgium, Netherlands and the Nordics. Delivery originates from our EU-based hub in Portugal, giving clients time-zone alignment across all these markets and EU-compliant delivery under GDPR (relevant for regulated data workloads in banking, healthcare, insurance and public sector). We also serve Iberian clients in Portugal and Spain, and support US clients on data application management engagements where remote delivery models fit.
Time to mobilise depends on the engagement model. Individual Specialists on Time & Materials typically start within one to two weeks of scope confirmation. Dedicated Teams stand up within three to four weeks. Managed Teams and Application Management engagements are structured over four to six weeks. This matters because UK employers consistently rank data engineering among the hardest technical roles to fill, and local hiring cycles for senior data engineers regularly run six to eight weeks or longer. Our pre-validated nearshore bench removes that delay for standard profiles. And we respond to every enquiry within one business day.
Yes. Common intervention patterns include a Snowflake or Databricks environment set up without proper cost or governance guardrails, a DBT project that turned into a modelling monolith, a BI programme where dashboard sprawl outpaced the semantic model, or an MDM programme with unclear ownership of the golden record. A senior data architect enters mid-flight, runs an architectural review focused on the real bottleneck, and re-establishes governance and delivery discipline. Mobilisation in one to two weeks. The engagement can start as an Individual Specialist architect review and scale into a Dedicated Team once the reset is agreed.
Yes. The nine roles on this hub deliberately span both. Modern stack coverage sits in Group 1 (Data engineers, Analytics engineers with DBT, Snowflake, Databricks) and Group 2 (Power BI, Tableau). Traditional coverage sits in Group 3 (Data architects, MDM consultants, Database administrators for Oracle, SQL Server and PostgreSQL). Most enterprise data estates are hybrid: a Snowflake or Databricks platform for new analytics and AI workloads, with legacy Oracle or SQL Server systems still running critical operational data underneath. Splitting modern and traditional across separate providers creates coordination overhead at exactly the wrong moment.
Data engineers own the pipeline layer: ingestion, ETL/ELT, orchestration with tools like Airflow or Dagster, streaming with Kafka, and the platform-native pipeline work in Snowflake or Databricks. Analytics engineers own the transformation layer that sits above the pipelines: DBT models, semantic definitions, medallion architectures (bronze, silver, gold layers) and the analytics-as-code discipline. Data engineers make sure the data lands reliably. Analytics engineers make sure the data lands as trustworthy business logic. Most modern data teams pair the two roles rather than choosing between them.
Yes. Data architects own the governance framework layer (data modelling standards, reference architecture, data mesh and data-as-a-product patterns). MDM consultants own the master data layer (golden record design, workflow, data quality controls, and non-SAP MDM platforms such as Informatica MDM, Reltio and Semarchy). If your master data programme sits inside SAP, the SAP MDG role lives under our SAP hub and combines cleanly with data architects from this hub for programmes that span both. Data governance is where most enterprise data initiatives succeed or fail, and staffing it right in the first phase matters more than most other decisions.
Let's Start the Data Conversation
Whether the outcome is a Snowflake or Databricks build, a DBT modelling programme, a Power BI or Tableau rollout, an MDM stand-up, or a single senior data architect to reinforce a workstream, our data bench is ready. Tell us your challenge and we respond within one business day.