Senior Data Architect

4 weeks ago

Norwich, Norfolk, United Kingdom Baldwin Risk Partners Full time

Why MSI? We thrive on solving complex challenges. As a leading MGA, MSI combines deep underwriting expertise with insurer risk capacity to create specialized insurance solutions that empower distribution partners to meet customers' unique needs. We have a passion for crafting solutions for the important risks facing individuals and businesses. Our company offers an expanding suite of products – from fully-digital embedded renters coverage to high-value homeowners insurance to sophisticated commercial coverages, such as cyber liability and habitational property – delivered through agents, brokers, wholesalers and other brand partners.

We prioritize exceptional service and rapid resolutions through our dedicated team. Our advanced technology platform simplifies the insurance experience, supporting every phase of the policy lifecycle. We're driven to build better insurance solutions.

The Senior Data Architect will oversee the design, development and optimization of our data orchestration and data pipeline architecture, ensuring seamless data collection and flow for cross-functional teams.

The ideal candidate is an experienced technical leader with a strong background in data engineering and architecture. This role requires a deep understanding of data management principles as they apply to scalability and design of dynamic, flexible data systems. The Senior Data Architect will also mentor junior engineers and provide technical guidance and a 'design thinking' perspective to the team.

Key Responsibilities:

  1. Maintaining and updating our Data Engineering Architecture.
  2. Designing and implementing ELT and ETL processes.
  3. Create and maintain optimal data orchestration architecture to support data initiatives.
  4. Provide thought leadership to improve implementation approaches and drive increased velocity of delivery.
  5. Assemble large, complex data sets that meet functional and non-functional business requirements.
  6. Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability.
  7. Build the infrastructure required for optimal extraction, transformation, and ingestion of data from various sources using SQL, Azure Data Factory, Spark/Synapse technologies.
  8. Support analytics tools that utilize the data pipeline to provide actionable insights into key business performance metrics.
  9. Work with stakeholders to assist with data-related technical issues and support their data infrastructure needs.
  10. Create data tools for analytics and data scientist team members to assist them in executing and optimizing data projects.
  11. Collaborate with colleagues to collect and structure data.

Data Management and Collection:

  1. Collect, audit, compile, and validate data from multiple sources.
  2. Communicate with internal teams and external partners to collect and validate data.
  3. Apply advanced knowledge and understanding of concepts, principals, and technical capabilities to manage a wide variety of projects.
  4. Recommends new practices, processes, and procedures.
  5. Provides solutions that may set precedent or have significant impact.

Requirements:

  1. Bachelor's degree in a related field preferred, equivalent years' experience considered.
  2. At least seven to ten years of data-related or analytical work experience in a data engineering or architecture role.
  3. Experience building and optimizing 'big data' data pipelines, architectures, and data sets.
  4. Advanced working SQL knowledge and experience working with relational databases, query authoring.
  5. Advanced understanding of and experience implementing data lakes, lake houses.
  6. Solid experience with SPARK (PySpark) language, and data processing techniques.
  7. Solid understanding of and experience with AZURE SYNAPSE tools and services.
  8. Some knowledge of Python preferred.
  9. Strong analytic skills related to working with structured, semi-structured, and unstructured datasets.
  10. Build processes supporting data transformation, data structures, metadata, dependency, and workload management.
  11. A successful history of manipulating, processing, and extracting value from large disconnected datasets.
  12. Strong project management and organizational skills.
  13. Experience supporting and working with cross-functional teams in a dynamic environment.
  14. Insurance industry experience preferred.

Work Environment:

Fast-paced, multi-tasking environment.

Important Notice:

This position description is intended to describe the level of work required of the person performing in the role and is not a contract. The essential responsibilities are outlined; other duties may be assigned as needs arise or as required to support the organization. All requirements may be modified to reasonably accommodate physically or mentally challenged colleagues.

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