Senior Data Engineer

At ICIS, our mission is to optimize the world's resources. We help companies make strategic, sustainable decisions by bringing transparency to markets across the world. We create a comprehensive view of commodities markets, providing companies with the data and intelligence to successfully navigate across global value chains every day. Our customers benefit from instant access to price assessments, reports and forecasts, a dedicated news channel and supply and demand data. You can learn more about ICIS at the link at: https://www.icis.com/explore.

You'll be joining a collaborative, high-performing team with deep technical and domain expertise. We work closely with Data Analysts and Data Scientists across a range of business areas, turning complex requirements into scalable, reliable data solutions. Our team plays a central role in ingesting and managing many of the organisation's key datasets. The data pipelines we build and maintain serve as the backbone for the insights delivered to our customers. Open communication, knowledge sharing, and a strong sense of ownership are core to how we work. With a strong focus on delivering the right data at the right time, this is a great opportunity to be part of a team where your work directly contributes to meaningful outcomes for our customers.

We have an outstanding opportunity available for a senior data engineer within our data operations team. This role will collaborate with stakeholders across business units to design, develop, and maintain the data pipelines, ensuring data quality which provides customers with the 'Right Data at the Right Time'.
This is an exciting opportunity to be part of a strategic transformation focused on data and AI innovation within a dynamic market-leading global business. We have a supportive culture with a keen focus on innovation, technical excellence, career development and mutual support.

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• Data Pipeline Development: Design, develop, and optimize robust data pipelines and ETL processes to ensure efficient data flow and integration
  
• Data Infrastructure Management: Manage and enhance our data infrastructure to support performance, scalability, and long-term reliability
  
• Advanced Analytics Support: Build and maintain data models, data marts, and data lakehouse architectures to support data science initiatives, advanced analytics and reporting
  
• Data Quality Assurance: Implement data quality checks to maintain accuracy and consistency across all data sources
  
• Technology Exploration: Explore and implement advanced data technologies and tools
  
• Drive Continuous Improvement: Identify opportunities to streamline processes and improve the efficiency of our data pipelines
  
• Mentor and Support Team Members: Provide guidance and mentorship to junior engineers and support team to tackle technical challenges together
  
• Stakeholder Collaboration: Work closely with cross-functional teams to understand data requirements and deliver solutions that meet business needs and collaborate with Analysts, Data Scientists, product owners, and business stakeholders to deliver high-impact, AI-driven solutions.
  

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• Considerable experience in Data Engineering with strong focus on Data Management and Data Quality
  
• Bachelor's Degree (Engineering/Computer Science preferred but not required); or equivalent experience required
  
• Deep proficiency in Python, SQL, Cloud Platforms ((AWS, GCP, Azure). Data Warehousing (Snowflake), Orchestration (Airflow, Rundeck), Streaming (Kafka)
  
• Continuous engagement with Data Science and Analytics colleagues to understand requirements for our data-assets and empower them with best possible data, to create high value analytical services
  
• Ownership of assigned data products, including data model design, end-to-end data pipeline delivery, data product quality monitoring, requirements analysis and issue resolution
  
• Enthusiastic attitude to explore and implement advanced data technologies and tools
  
• Working with other tech teams to define data requirements for external data products e.g., APIs, Data Marketplace offerings etc.
  
• Create data-to-value framework, which enables data value tracking from ingestion to customer value realisation
  
• A team player who works collaboratively and possesses excellent communications skills with ability to communicate technical details in business terminology
  
• Demonstrated success in managing multiple deliverables concurrently and prioritising effectively
  
• Detail-orientated with strong problem-solving skills, innovative thinking and self-motivation in learning and exploring applications
  
• Capable of providing coaching and support to transfer technical and data knowledge, fostering a collaborative team environment
  
• Contribute to continuous improvement initiatives and process enhancements.
  

Learn more about the LexisNexis Risk team and how we work