Data Engineer / Senior Data Engineer

Our client, a high growth Medical Technology company focused on the area of Robotics.

Based in UK, they are leading the way for businesses within this highly specialised area and their goal is to help transform people's lives across the globe.

As a Senior Data Engineer, you'll be responsible for:

• Taking a leading role in the development effort to meet data engineering project requirements as well as providing creative solutions to problems.

• Owning, managing and delivering small projects as the technical lead in a growing team, having the willing-ness to take responsibility and manage own time and tasks.

• Conceptualising the design specifications for each project and working with others to establish user or customer requirements, project costs and resources.

• Building creative and world-class data engineering solutions to support business intelligence including data lakes, cloud based ETL pipelines, data warehouses and architecture, SQL and non-SQL databases, KPIs, trends/forecasts, logistic regression, anomaly detection techniques and graphing/dashboarding.

• Curating complex datasets including robotic telemetry data, clinical outcome data, video data, business intelligence and much more.

• Designing and building ETL pipelines to include data from a wide variety of sources including RDS, non-relational databases and object data stores, e.g. AWS S3, Hadoop.

• Supporting the needs of our team of data scientists and machine learning scientists/engineers by providing optimised datasets and pipelines.

Requirements to a Senior Data Engineer:

• Broad expertise in data lakes, ETL pipelines, data warehouses and architecture, SQL and non-SQL databases, big data analysis and architecture.

• Experience in applying modern techniques to business intelligence analysis, including performance metrics and benchmarking (KPIs etc), trends/forecasts, logistic regression, statistical analysis, data mining and anomaly detection techniques.

• Experience with modern cloud services, e.g. AWS services EC2, RDS, Redshift, S3, Glue, Athena, and Lambda.

• Experience with big data tools and technologies, e.g. AWS EMR, Hadoop/Spark, Kafka

• Proficiency in at least one relevant modern object-orientated or functional programming language, preferably Python.

• Knowledge of standard libraries and frameworks, e.g. Numpy, Scipy, Pandas, Matplotlib, Tensorflow, Keras and PyTorch.

Additional Keywords: data science, machine learning, supervised, unsupervised, reinforcement learning, deep learning, computer vision, statistics, signal processing

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