Data Engineer, AND Digital

• Experience of using modern and traditional data technologies including: MongoDB, PostgreSQL, mySQL/mariaDB, Kafka, Splunk/ELK or other logging and monitoring tools, BI and Data Warehousing solutions and ETL and migration technologies
• Experience with Snowflake, Sigma and Fabric
• Good cloud-native data engineering skills e.g. AWS RDS, Redshift, Kinesis, Glue or Azure CosmosDB, DataFactory, SQL DB etc
• Good experience in quality assuring data programmes, including non-functional testing and performance tuning
• At least 3 years experience writing Python, R, SQL or Scala
• Experience in Dimensional modelling and Data Warehouse patterns
• Good understanding and track record of delivering complex data solutions using Agile methods including Scrum, SAFe etc
• Hands-on experience of modern software delivery, including CI/CD and DevOps practices
• Experience with Big data storage or Data Lakes
• A keen understanding of industry best-practice around standards, quality and continuous improvement in the field of Data Engineering
• Experience in the field of Data Engineering, Science or Analytics

Desirable

• As a Senior Data Engineer, you will spend your time helping clients achieve their data engineering needs. Primarily the development, deployment and maintenance of data pipelines in a fast moving, Agile environment
• You’ll also make a real impact by taking an active role in the team’s Agile Development practices, technical decision making and development, generating value and continuously striving to improve the quality and reliability of our data and processes
• You will spend the majority of your time helping deliver client data engineering opportunities and supporting the growth of our junior-mid level technologists; both within AND and for our clients
• Extract data from multiple data sources
• Write code to ingest or transform new and existing data
• Transform data in various ways to support data scientists and product analysts
• Build and design a scalable and extensible data architecture
• Conduct large scale batch and real-time processing from varying sources
• Influence the client on how they approach data engineering issues
• Collaborate with tech leads on system integrations
• Influencing technical direction:
• Engaging actively with our Consultancy Data Strategy and Insight practice, to help define and materialise clients’ data strategies
• Championing and upholding high technical quality standards