As a Senior Data Engineer, you will be working as part of a multidisciplinary team to build solutions that make data accessible to enable solutions to be optimised by using an evidence-based approach. Engaging with our clients you will design and implement data solutions ensuring solutions are integrated with internal systems and business processes. Your role in a nutshell: Act as an SME within the Hippo squad to lead, design and implement data solutions that meet business requirements. Help architects realise data system design such as Meshes, Warehouses and Event based systems Implement data flows to connect operational systems, data for analytics and business intelligence (BI) systems Re-engineer, develop and optimise code to ensure processes perform optimally Build great relationships with your team and stakeholders Work with the Hippo community to share best practice to ensure high standards Involved in the recruitment and on-boarding of other engineers, and support other consultants in their professional development Promote Hippo’s Engineering Herd internally and externally (for example through writing Blogs, Workshops, Seminars or Conferences) About the Candidate: Proven track record in Snowflake, Python, dbt, AWS and Terraform Proficiency in R, Bash, Java/.NET and/or PowerShell desirable Broad knowledge across cloud architectures, networking and distributed computing systems Experience of data system design such as Data Lakes, Data Meshes and Data Warehouses. Experience of a wide range of data sources, SQL, NoSQL and Graph. A proven track record of infrastructure delivery on any data platform (Snowflake, Elastic, Redshift, Data Bricks, Splunk, etc). Strong and demonstrable experience writing regular expressions and/or JSON parsing, etc. Strong experience in log processing (Cribl, Splunk, Elastic, Apache NiFi etc.) Expertise in the production of dashboard/insight delivery Be able to demonstrate a reasonable level of security awareness (An understanding of basic security best practices, OAuth, MFA, TLS, etc.) Experience in the processing of large datasets A firm understanding of data modelling and normalisation concepts Good estimation skills for times, latencies and costs. Experience working within multidisciplinary teams desirable Teamwork and presentation skills, experience of mentor led working practices
