Lead Data Engineer

1 day ago

Luton, United Kingdom Advantage Resourcing Full time

Job Title: Lead Data Engineer Pay Rate: Negotiable Contract Length: 6 months Location: Luton (on-site requirement - 2/3 days a week) Advantage Resourcing are working in partnership with a well-known brand who are currently recruiting a Technical Lead. - Serve as the technical expert responsible for designing production-grade Data solutions, serving the myriad of descriptive, predictive and prescriptive use-cases across the core business functions, Data Science and Analytics. - Accountable for preparing and maintaining design artefacts for IT Data Engineering solution designs, including AS-IS, TO-BE and transitional states, guaranteeing they meet the functional and non-functional requirements: exhibiting high levels of performance,security, scalability, maintainability, appropriate reusability. - Responsible for verifying requirements, defining the Data Engineering components, developing an implementation and QA approach, providing thought leadership for all data solutions. - Provide guidance and technical assurance to engineers, ensuring consistency and conformity to agreed standardsand quality; actively contributing to all stages of the development lifecycle - cradle-to-grave. - Support the Data Architect to shape the future of the data domain and aid in landing new "data" capabilities into BAU - considering people, process and technology. - Support solution architects in the creation of end-to-end design architecture. Accountable for the related technical design and any amendments resulting from Technical Design Assurance (TDA). Skills required: - Solid understanding of data concepts and data modelling principles; applied across traditional warehousing, OLTP and also modern data lakes. - Proficient in Apache Spark or any other distributed data programming frameworks (e.g. Flink, Arrow, MapR).> - Experience with designing and building real-time pipelines, leveraging message brokering and stream processing technologies (Kinesis, Kafka, RabbitMQ, Flink, Spark Streaming). - Strong SQL background - comfortable writing efficient SQL (Transact-SQL, Hive -HQL) to meet the requirement. - Commercial experience of building and architecting scalable Extract Load Transform (ELT) data pipeline implementations at varying frequencies - batch, near-real-time and real-time, from a myriad of source types - relational, non-relational, API, streaming(e.g. Kafka topic) - Experience with Apache Airflow/Spring DataFlow, Control-M, or a similar orchestration tool in a Production setting. - Strong understanding of Data Management principles (security and data privacy) and how they can be applied to Data Engineering processes/solutions, e.g. access management, data privacy, handling of sensitive data (e.g. GDPR) - Experience working with a combination of cloud-based big data technologies (HDFS, Blob Storage, - Understanding of Data Science Tooling for ML (e.g. MLFlow, Sagemaker) and interactive API's/Web Apps (e.g. R-Studio, Shiny, Flask, Django). - Experience with Data Analytics Tooling for dashboarding and visualisation (e.g. Tableau, Looker, (SQLAnalytics), Power BI). - Experiencing working with containerisation solutions in a data context, e.g. Kubernetes. Reference: 63005

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