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EXL

Analyzes business data and runs outsourced operations

Data Architect - Azure Databricks, Specialty Insurance

Data ManagementConfirmed live in the last 24 hours
Full-timeLondon, UK

About the Job

Requirements

  • At least 8 years of experience in data architecture, data modelling, or a similar field, including hands-on use of a data modelling tool such as Erwin, ER/Studio, or PowerDesigner.
  • Prior experience in commercial or specialty insurance, ideally the London Market, with familiarity with Lloyd’s, bordereaux, reinsurance, or regulatory and actuarial reporting.
  • Hands-on experience designing solutions on Azure Databricks, including Delta Lake, Unity Catalog, Spark (PySpark and Spark SQL), and Databricks SQL.
  • Experience with core Azure data services and their integration with Databricks, such as ADLS Gen2, Azure Data Factory, Microsoft Entra ID, Key Vault, and secure networking.
  • Demonstrable experience of dimensional modelling and layered architecture patterns such as Medallion, with a strong understanding of data warehousing and OLTP systems from an integration perspective.
  • Strong SQL skills, including writing procedures, views, and functions for data analysis, profiling, and quality checks.
  • Proficiency in Python or a similar language and experience with orchestration and transformation tooling such as Databricks Workflows, Lakeflow Declarative Pipelines, Azure Data Factory, or dbt.
  • Experience designing metadata-driven data ingestion or ELT frameworks.
  • Experience working with data formats, including row-based and columnar storage, Delta and Iceberg table formats, and common file formats such as CSV, XML, and JSON.
  • Experience applying data governance and security practices on a lakehouse platform, including access control, lineage, and data quality frameworks.
  • Client-facing experience, including stakeholder management and presenting designs to technical and non-technical audiences.
  • Technical leadership experience, such as mentoring, leading design reviews, and guiding delivery teams.
  • A Bachelor's degree or equivalent experience.

Responsibilities

  • Design the lakehouse architecture on Azure Databricks using Delta Lake and the Medallion pattern, with bronze, silver, and gold layers organized by data quality and purpose to keep the platform scalable and maintainable.
  • Design and apply dimensional models, including star and snowflake schemas, and use approaches such as ODS and Data Vault modelling where they suit the client’s needs.
  • Create and maintain conceptual, logical, and physical data models with corresponding metadata that translate business needs into long-term solutions, covering insurance domains such as policy, premium, claims, exposure, reinsurance, and finance.
  • Design gold-layer consumption models and, where Power BI is the consumption layer, semantic models served from Databricks SQL for efficient reporting and self-service analytics.
  • Select and design appropriate storage and exchange formats for each workload, including row-based and columnar storage, Delta and Iceberg table formats, and file and message formats such as Parquet, CSV, Excel, XML, JSON, and Protobuf.
  • Optimize platform performance and cost through decisions about partitioning versus liquid clustering, file sizing, Photon, and cluster and SQL warehouse sizing.
  • Manage the model lifecycle by optimizing and updating models for new and existing client projects, reverse engineering physical models from existing databases and SQL scripts, and recommending opportunities for reuse.
  • Map business processes to conceptual models, using techniques such as bus matrices to identify dimensions, facts, and conformed dimensions.
  • Help set the client’s data architecture direction, including platform and technology choices across the Azure data estate, and document the rationale and trade-offs.
  • Design and oversee metadata-driven data ingestion frameworks on Databricks, using configuration rather than bespoke code to onboard new sources, handle schema changes, and apply consistent patterns for loading, logging, and data quality checks.
  • Define how data flows from source systems, including policy administration, claims, finance, bordereaux, and market data feeds, through to the consumption layer, resolving integration challenges along the way.
  • Perform data analysis and profiling to support mapping and transformation from legacy systems and spreadsheets to target models; validate data against business rules and source systems for accuracy and completeness; and define the testing approach for data pipelines and models.
  • Develop and document naming conventions, coding practices, modelling standards, and metadata management procedures, and evaluate data models and physical databases for variances against them.
  • Define the data governance and security approach using Unity Catalog, including catalogue and schema design, role-based access control integrated with Microsoft Entra ID, row- and column-level security, data masking, lineage, tagging, and data quality frameworks appropriate to sensitive and regulated insurance data.
  • Produce architecture deliverables such as solution designs, architecture decision records, and roadmaps that account for client constraints such as security policies, data residency requirements, and regulatory obligations.
  • Work with application development and data engineering teams to implement data strategies and build data flows, guiding them on project limitations, capabilities, performance requirements, and interfaces.
  • Define CI/CD and environment promotion patterns for the platform using Git, Databricks Asset Bundles, and infrastructure as code such as Terraform and Azure DevOps.
  • Lead design workshops and coordinate with project managers and client business and technical staff, building trusted relationships and presenting recommendations to senior stakeholders.
  • Support scoping, estimating, and solution input for new and existing engagements.
  • Mentor and coach team members and provide line management where the engagement requires it.

Desired Qualifications

  • Experience in a consultancy or professional services environment, working across multiple clients or engagements.
  • Databricks certification, such as Data Engineer Associate or Professional, or Azure Databricks Platform Architect.
  • Experience designing gold-layer semantic models for Power BI, including how model design affects report performance.
  • Line management experience.
  • A Master's degree.
  • Experience with Databricks Asset Bundles, Terraform, and CI/CD for data platforms and data model changes.
  • Experience with Delta Sharing, Lakehouse Federation, or real-time and streaming workloads.
  • Exposure to machine learning and AI workloads on Databricks, such as MLflow or Mosaic AI.
  • Experience with other modern data platforms, such as Microsoft Fabric, Azure Synapse, or Snowflake, or other clouds such as AWS or GCP.
  • Experience with enterprise cataloguing and metadata management tools beyond Unity Catalog, such as Microsoft Purview or Collibra, and designing metadata repositories and standards.

About the Company

EXL

Analyzes business data and runs outsourced operations

EXL analyzes business data and runs outsourced operations for insurers, healthcare payers, banks, retailers, and other large organizations. Its teams combine industry expertise with data engineering and AI to handle tasks such as claims processing, payment reviews, customer service, and finance within existing technology environments. The company also builds software, including LifePRO, which manages insurance policies, and EXLdata.ai, which connects fragmented data for use in AI systems. Clients pay for consulting projects, ongoing managed services, and software delivered through the cloud. EXL was founded in 1999 and is headquartered in New York City.

Company size
10,001+
Company stage
IPO
Headquarters
New York City, New York
Founded
1999

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