About Us Ascent is now part of Acuity Analytics, marking an exciting new chapter with strong global reach, an impressive client base, and ambitious growth plans. Together, we deliver cutting-edge data and digital transformation solutions to high-growth and regulated organisations—combining talent, technology, and deep domain expertise to drive real business impact. About the Role We’re looking for a (Senior) BI & Data Engineer to support global claims reporting for a leading reinsurance organisation. You’ll work at the intersection of Power BI and Azure Databricks, building scalable data models and high-impact dashboards that serve as a single source of truth for the business. Key Responsibilities Power BI & Analytics - Build and enhance Power BI dashboards, datasets, and semantic models - Apply best-practice data modelling (star schema, conformed dimensions) - Develop DAX measures for key claims KPIs (incurred, paid, reserves, etc.) - Optimize performance (efficient models, DAX tuning, incremental refresh) - Ensure consistent metrics across all reporting Databricks & Data Engineering - Work with Azure Databricks (Delta Lake) as the core data platform - Support development of curated data layers (Silver / Gold) - Build SQL / PySpark transformations for reporting - Ensure data quality, reconciliation, and traceability - Follow governance standards and collaborate with data teams Collaboration & Delivery - Partner with Product Owners and stakeholders - Turn business needs into scalable BI solutions - Contribute to agile delivery (sprints, backlog, documentation) - Share knowledge and best practices across the team Skills Required - Strong Power BI experience (data modelling, DAX, performance tuning) - Solid experience with Azure Databricks (PySpark and/or Spark SQL) - Good understanding of Delta Lake and medallion architecture - Strong SQL and data warehousing knowledge - Experience working with large, complex datasets - Comfortable in international, stakeholder-heavy environments Nice to Have - Insurance / reinsurance or claims reporting experience - Knowledge of data governance, data products, or data mesh - Exposure to financial or actuarial reporting - Experience with DevOps / CI-CD (Power BI or Databricks) Ways of Working - Agile environment - Collaborative, team-focused culture - Strong focus on quality, ownership, and delivery If you’re excited about building modern data platforms and delivering meaningful insights at scale, we’d love to hear from you. Why join us People are at the Heart of our Business.  By investing in people, we achieve exceptional results for our clients and create new opportunities for our teams to thrive.  Check out this page for more details. If you have any questions contact our Talent Acquisition team on ta.admin@acuityanalytics. For more details about life at Ascent, check out our Life Page here. For more details about Acuity Analytics please see here: Read here.

• 5+ years working on the role professionally. • Coding Python and use in data processing solutions and related data technologies like Pandas, and PySpark. • Consume data from different sources like REST APIs. • Work with relational and non-relational data stores (like: HBASE, Cassandra or MongoDB; S3, blobs). • Consumption; Design. • Data Streams (Kafka, Kinesis, Flume,) and message queuing (SQS, SNS, RabbitMQ, etc). • Ensure that the data model scales and enables high performance. • Distributed data stores. • Data/Stream processing (Spark, Flink, Hadoop). • Data pipelines, data ingestion pipelines, scalable streaming data pipelines processing. • ETL using solutions: Talend; Informatica; SQL Server Integration Services (SSIS). • Data warehouse (Snowflake, Redshift, Hive). • Implementation of data warehouse solutions, providing near real-time data to a variety of client systems; Using SQL databases to construct data storage. • Reporting / BI, design, implementation, and enhancement of BI tool is a plus. Looker; Power BI; Tableau. • Experience designing and implementing data applications and services on the public cloud, AWS, GCP, or Azure using PaaS platforms. • Familiarity with data privacy regulations and best practices.

• Hands-on development and optimization of the data backend, ensuring stability, performance, and architectural consistency • Build and optimize Snowflake data models and workloads (raw → curated → data products), with strong focus on performance and cost efficiency • Develop and maintain transformation logic in dbt (modeling, refactoring, tests, documentation, macros) to ensure data quality and scalability • Orchestrate reliable data pipelines using Airflow/Astronomer (DAG design, dependencies, retries, monitoring/alerting) for production readiness • Use Git + CI/CD to enforce code quality and enable automated testing and deployments across the data platform • Work with IT and business colleagues to develop solutions to specific problems that at times leverage existing solutions and systems • Build professional relationships with clients, management, and team members to ensure the delivery of proposed solutions

The Role We're looking for a product-minded Senior Data Engineer to lead the buildout of a new, greenfield enterprise data platform at Fusion. This is not a maintenance role. You will architect and own a new data platform product from the ground up-designing the infrastructure, pipelines, storage layers, and connectors that unify resilience data across customers, systems, and cloud environments. You will define how data is ingested, modeled, stored, governed, and exposed across Fusion's ecosystem. This platform will power next-generation analytics, intelligent functionality, integrations, and external data products. This is a high-ownership opportunity for someone who wants to build something foundational, influence architectural direction, and create a scalable data platform that becomes core to Fusion's long-term strategy. Key Responsibilities • Architect and build Fusion's next-generation enterprise data platform from the ground up, including data lake and warehouse components.• Design and implement scalable ETL/ELT pipelines to ingest and transform data from internal systems, customer environments, and third-party platforms.• Develop and/or leverage reusable ingestion frameworks and system connectors (e.g., Salesforce, ServiceNow, APIs, cloud storage, event streams).• Define data modeling standards, transformation layers, and storage strategies to support analytics, reporting, and product capabilities.• Establish best practices for data governance, quality, observability, lineage, and security across the platform.• Build backend services and APIs that expose data capabilities to downstream applications and products.• Partner with product and engineering leadership to shape the long-term data platform roadmap. Knowledge, Skills, and Abilities • Strong SQL expertise with experience designing performant data models and production-grade transformations.• Experience building data lakes, warehouses, and distributed data systems from the ground up.• Experience with one or more modern data platform technologies such as Snowflake, Databricks, AWS, Azure, or GCP.• Strong understanding of ETL/ELT patterns, orchestration, and pipeline reliability.• Experience designing and implementing enterprise system integrations and APIs.• Strong engineering fundamentals with focus on scalability, performance, monitoring, and security.• Experience with Salesforce or ServiceNow data models and integrations (bonus).• Strong Java skills or experience building backend services in Java (bonus).• Experience working in Azure environments (bonus).• Product-oriented mindset with the ability to make pragmatic architectural decisions in ambiguous, early-stage environments. Qualifications (Education and Experience) • Bachelor's degree in Computer Science, Engineering, Information Systems, or a related field.• 5+ years of experience in data engineering, backend data systems, or platform engineering roles.• Experience building or significantly expanding a data platform or data infrastructure in a production environment.• Experience working in cloud-native environments.• Experience designing enterprise-grade integrations and connectors.• Experience with Salesforce or ServiceNow integrations (nice to have).• Experience with Java-based services (nice to have).• Experience with Azure (nice to have). Milestones for the First Six Months In one month, you will: - Complete onboarding and gain deep familiarity with Fusion's products, architecture, and long-term platform vision - Assess the current state of data infrastructure and define a proposed architecture for the new platform - Align with product and engineering leadership on platform scope and priorities In three months, you will: - Deliver the first foundational components of the greenfield data platform (core storage layer, initial pipelines, and architecture patterns) - Implement initial ETL/ELT workflows and at least one production-grade system connector - Establish standards for modeling, governance, and observability In six months, you will: - Own and deliver the first production-ready version of Fusion's new data platform product - Have multiple ingestion pipelines and connectors operating reliably in production - Serve as the architectural owner of the platform, driving roadmap and technical direction - Propose and lead the next phase of platform expansion (scalability, performance optimization, advanced integrations) Compensation & Benefits The annual base salary range for this position is $135,000-$155,000, depending on the candidate's experience, qualifications, and relevant skill set. The position is also eligible for an annual bonus. Fusion offers a comprehensive benefits package including medical, dental, vision, and a 401(k) plan. Disclaimers Fusion is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, disability, age, pregnancy, military service or discharge status, genetic information, sex, sexual orientation, gender identity, or national origin. Nothing in this job posting should be construed as an offer or guarantee of employment.