Key skills
Amazon RedshiftAWSCloudDistributed SystemsETLKafkaPythonSparkSQLTableauAILLMRAGAgenticELTData EngineeringAnalyticsLookerBIPower BIRedshiftDatabricksS3GlueAthenaKinesisSaaSAgileCI/CDLeadershipCollaboration
About this role
Role Overview
- Design, build, and operate robust, scalable, and secure data pipelines and infrastructure, meeting defined performance, availability, and governance standards across the data stack
- Take hands-on ownership of data pipeline development, including batch and streaming workloads, from ingestion through to consumption
- Ensure consistently high standards of data quality, reliability, and availability across all data platforms
- Enable analytics and AI use cases through well-designed, well-governed data foundations and reusable data patterns
- Partner closely with Analytics Engineers and Data Analysts to support the creation of reliable, business-aligned datasets and models
- Collaborate with Product, Engineering, and Architecture teams to ensure data solutions align with platform strategy and product needs
- Contribute to the evolution of the company’s data architecture in collaboration with the Architecture Review Board, ensuring pipelines and data solutions align with established platform patterns, with a strong AWS-first approach
- Maintain and support existing data pipelines, including troubleshooting, bug fixing, and incremental improvements to ensure reliability and performance
- Ensure data operations comply with privacy, security, and regulatory requirements, embedding governance and access controls into data pipelines
- Monitor, maintain, and continuously improve data pipelines, infrastructure, and platform performance, including observability and alerting
- Maintain strong collaboration with Product, Engineering, and Domain Leadership (EHS, ESG, Chemical Safety), contributing to quarterly reporting and ensuring data initiatives remain aligned with company objectives
Requirements
- Typically 6+ years of experience in Data Engineering or similar roles
- Strong hands-on delivery in cloud-based environments
- Experience in SaaS, Health & Safety, ESG, or Chemical Safety domains is a plus
- Experience working in Agile environments with DevOps, CI/CD pipelines
- Strong delivery mindset with the ability to take data initiatives from design through production
- Advanced proficiency in Python and SQL
- Strong experience designing and operating ETL / ELT data pipelines at scale
- Hands-on experience with AWS-based data platforms, including: S3, Glue, Redshift, Athena, Kinesis
- Strong experience implementing Change Data Capture (CDC) patterns using Kafka and/or AWS Kinesis
- Strong experience working with large-scale structured and unstructured data
- Experience building and operating streaming and event-driven data pipelines
- Experience embedding security, access control, and compliance into data platforms (e.g. GDPR, enterprise data security best practices)
- Proven ability to design scalable and efficient data architectures, optimising pipelines and storage
- Experience working with LLMs and AI-enabled data pipelines, including preparing, governing, and serving data for LLM, RAG, and agentic workflows
- Familiarity with agentic development patterns and event-driven architectures that support AI-driven automation and decision-making
- Working knowledge of BI and analytics tools such as QuickSight (preferred), Power BI, Tableau, or Looker
- Experience with distributed systems and modern data platforms (e.g. Spark, Databricks)
Tech Stack
- Amazon Redshift
- AWS
- Cloud
- Distributed Systems
- ETL
- Kafka
- Python
- Spark
- SQL
- Tableau
Benefits
- Generous Paid Time Off
- Extended Parental Leave
- Robust Health Coverage
- Accelerated Learning Paths
- Team Wellness Initiatives
- Company-wide Events
- Employee Resource Groups
- Recognition awards