• Design, develop, and deploy scalable ETL/ELT pipelines and APIs for ingestion and transformation. • Implement data modeling best practices for optimal accessibility, flexibility and query performance. • Implement data governance practices, including data security, privacy, and compliance, to ensure data integrity and regulatory compliance. • Work closely with cross-functional teams, including product managers, designers, and other engineers, to ensure seamless product development from concept to deployment. • Influence product and cross-functional teams to identify data opportunities to drive impact. • Stay updated with the latest industry trends and technologies, ensuring our tech stack remains modern and competitive. • Build monitor and alerts for data pipelines monitoring, identify and resolve performance issues, troubleshoot data-related problems in collaboration with other teams, and ensure data platform SLAs are met.

• Lead the handover from the external implementation partner • Become the primary internal expert and own the Microsoft Fabric BI platform • Ensure the platform is robust, secure, scalable, and well‑documented • Own and develop Fabric Data Factory pipelines and ingestion patterns • Build and maintain PySpark / Spark SQL notebooks • Implement validation, reconciliation, and anomaly‑detection checks • Design and maintain Semantic Models (measures, relationships, RLS, Direct Lake)

Role Description You will join one of our high-performing consultant teams, delivering cutting-edge solutions for our financial services clients. This is a hands-on role where your data analysis skills and financial acumen will be essential to supporting senior business experts. You will be moving beyond the limitations of standard tools like Excel to solve complex data challenges. Working directly with critical data in the reinsurance domain, performing data crunching & providing actionable insights that inform key decisions. Key Responsibilities - Perform complex data manipulation and analysis to support senior business experts and stakeholders. - Utilise Python and its data libraries to handle large datasets and automate analytical tasks. - Design and execute robust data mapping and analysis projects. - Work with our expert teams to understand client needs and translate them into effective data solutions. - Working in a fast paced start-up agile and high pressure environment. - DBT: Transforming raw data in the warehouse into clean, tested & documented models using SQL. - Databricks: Must have recent experience. - Domain knowledge: Have worked within the operations team for an asset management department and understands assets data, like financial securities, trading data within the last 3 years. - Investment & Financial: Experience with investment-related projects or working in the reinsurance or life insurance domain. - SQL: Data manipulation and querying. - Python: Experience in libraries like Pandas and NumPy. - Communication: Excellent senior stakeholder, articulate, presenting & engagement skills. Requirements - Fully Remote - Outside IR35 - Long term contract - c£500/Day

Company Description About Syngenta At Syngenta Crop Protection, we're pioneering solutions that safeguard global food security while championing sustainable agriculture. As a world market leader headquartered in Switzerland, we empower farmers with innovative crop protection technologies that defend against nature's toughest challenges. We unite advanced science with digital solutions to develop intelligent crop protection that maximizes yields while minimizing environmental impact. Join our mission of revolutionizing plant protection from seed to harvest. Job Description Support analytical data infrastructure providing application, tool, and ad-hoc access to large datasets consisting of complex data types including genomic, phenotypic, environmental, image and geospatial data. Engage with business stakeholders to understand strategic roadmaps and build a technical strategy to support them. Interface with DevOps teams to extract, load, and transform data from a wide variety of data sources using big data technologies. Deploy high value, high performance datasets. Create and support real-time data pipelines built on AWS technologies. Embed quality and intelligent reporting capabilities into data pipelines including detection of anomalies and changes in trends with meaningful alerts and statistics. Provide new capabilities and increase efficiency by continually researching the latest big data and visualization technologies. Collaborate with data scientists and other tech teams to implement advanced analytics algorithms into data pipelines that exploit rich datasets for statistical analysis, prediction, clustering, and machine learning. Improve automation and simplifying data as a service. Role is fully remote. Qualifications This position requires a Bachelor’s degree in Engineering (Any), Computer Science, or a related field of study and five (5) of experience in the position offered or five (5) years of experience as a Data Engineer, Software Engineer, Technology Analyst, or a closely related occupation. Requires five (5) years of experience with: - Working with business and technical stakeholders to implement end‐to‐end data solutions including data models, data pipelines, and business intelligence products - Designing and implementing DW Architectures, OLAP technologies, Star schema, Snowflake schema, and Aggregation Techniques. - Gathering requirements and building custom BI and big data reporting solutions using Tableau, OBIEE, Looker, or PowerBI. - Architecting database management systems with Oracle, SQL Server, Postgres, Spark, or Hadoop. - Working with data structures and algorithms. - Programming and scripting languages including Shell, Python, Scala, or PySpark. Requires three (3) years of experience with: - Designing and building real time analytics platform with latencies less than a minute using Kafka, Spark, AWS, or GCP. - Working with Datadog to identity issues with data quality and anomalies, and setup alerting. - Setting up custom frameworks to identify data quality issues and introduce self-service Business Intelligence capabilities using CI/CD tools including Buildkite, Jenkins, or Gitlab. - Collaborating with Data Scientists and building data products that help machine learning teams in clustering, prediction, and statistical analysis. - Building data pipelines to extract load and transform data using big data technologies including BigQuery, Redshift, BigTable, Aerospike, Dataproc, or EMR. - Must pass a background check and drug test before beginning employment. Additional Information What We Offer: - A culture that celebrates belonging and collaboration, promotes professional development, and strives for a work-life balance that supports the team members. offers flexible work options to support your work and personal needs - Full Benefit Package (Medical, Dental & Vision) that starts on your first day. - 401k plan with company match, Profit Sharing & Retirement Savings Contribution. - Paid Vacation, 9 Paid Holidays, Maternity and Paternity Leave, Education Assistance, Wellness Programs, Corporate Discounts, among other benefits. Syngenta is an Equal Opportunity Employer and does not discriminate in recruitment, hiring, training, promotion or any other employment practices for reasons of race, color, religion, gender, national origin, age, sexual orientation, marital or veteran status, disability, or any other legally protected status. Family and Medical Leave Act (FMLA) (http://www.dol.gov/whd/regs/compliance/posters/fmla.htm) Equal Employment Opportunity Commission's (EEOC) (http://webapps.dol.gov/elaws/firststep/poster_direct.htm) Employee Polygraph Protection Act (EPPA) (http://www.dol.gov/whd/regs/compliance/posters/eppa.htm) #LI-DNI