Senior Engineer, Data Engineering

2 weeks ago

London, Greater London, United Kingdom Axtria - Ingenious Insights Full time
Axtria is a global provider of cloud software and data analytics to the Life Sciences industry.

We help Life Sciences companies transform the product commercialization journey to drive sales growth and improve healthcare outcomes for patients.

Since our founding in 2010, technology innovation has been our winning differentiation, and we continue to leapfrog competition with platforms that deploy Artificial Intelligence and Machine Learning.

Our cloud-based platforms - Axtria DataMax, Axtria InsightsMax, Axtria SalesIQ, and Axtria MarketingIQ - enable customers to efficiently manage data, leverage data science to deliver insights for sales and marketing planning and manage end-to-end commercial operations.

With customers in over 75 countries, Axtria is one of the largest global commercial solutions providers in the Life Sciences industry.

We continue to win industry recognition for growth and are featured in some of the most aspirational lists - INC 5000, Deloitte FAST 500, NJBiz FAST 50, SmartCEO Future 50, Red Herring 100, and several other growth and technology awards.

Axtria Institute, our in-house university, offers the best training in the industry and an opportunity to learn in a structured environment.

A customized career progression plan ensures every associate is setup for success and able to do meaningful work in a fun environment.

We are seeking a highly skilled and experienced Data Engineer to join our team.

The ideal candidate will have 5-7 years of recent experience in data engineering and hold a Bachelor's Degree or higher in Computer Science or a related field.

The Data Engineer will be responsible for designing, developing, and maintaining data pipelines and systems in Azure Cloud environments, with a strong emphasis on Azure Data Lake, Azure Data Factory, and Microservices architecture.

Develop and maintain data pipelines in Azure Cloud environments, leveraging Azure Data Lake, Azure Data Factory, and Microservices architecture.

Design and implement scalable and efficient data processing solutions using technologies such as ServiceBus, REST API, App Service, SQL Data Warehouse, and Data Mart.

Utilize Vector Databases, Cosmos DB, Redis, and Elasticsearch for efficient data storage and retrieval.
Demonstrate proficiency in programming languages including Python, Spark, Databricks, Pyspark, SQL, and ML Algorithms.
Implement Machine Learning models and algorithms using Pyspark, Scikit Learn, and other relevant tools.
Manage Azure DevOps, CI/CD pipelines, GitHub, and Kubernetes (AKS) for efficient software development and deployment.
Implement ML/OPS solutions using Azure ML, Databricks MLFlow, and LLMOps for streamlined Machine Learning operations.
Ensure data governance and data cataloging standards are maintained, utilizing tools such as Collibra and Talend Data Catalogue.
Collaborate with stakeholders to develop visualization and reporting solutions using Power BI, Tableau, and front-end frameworks like React.
Run tests to assess KPI performance and troubleshoot and address problems with deployed models to improve user experience.
5-7 years of recent experience in data engineering.
~ Bachelor's Degree or higher in Computer Science or a related field.
~ Experience with Vector Databases, Cosmos DB, Redis, Elasticsearch.
~ Strong programming skills in Python, Spark, Databricks, Pyspark, SQL, ML Algorithms, Gen AI.
~ Knowledge of Azure DevOps, CI/CD pipelines, GitHub, Kubernetes (AKS).
~ Familiarity with data governance, data cataloging tools (Collibra, Talend Data Catalogue).
~ Experience with visualization and reporting tools like Power BI, Tableau, and front-end frameworks such as React.

Master's Degree in Computer Science or a related field.
Experience working in Agile development environments.

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