Company Overview
Coronado Research is a consultancy-led, professional services organisation, which provides support to pharmaceutical, biotechnology, and medical device companies. Our objective is to optimise the clinical development process by leveraging all the data available using AI, ML, and leading technologies. Our practices cover Regulatory Strategy, Advanced Analytics, Market Access and Health Economics, and Technology. Our teams work with customers to “join-the-dots” between these disciplines to ensure treatments are developed with the end in mind and better match market needs.
About the job
Are you an experienced data engineer a strong skill-set including; Azure, SQL, ADF, ETL, Rest API + Proven DWH Development experience? We are looking for a passionate technologist who is curious about data, insights and innovation.
We’re supporting a client in their search for a senior data engineer to systematically source internal data in order to be able to drive reporting and analytics internally for the business. You should have a storng background in data warehousing and techniques such as Kimball.
Note this is a permanent full-time position working directly for our client in the UK and it is a fully remote position
This role would suit:
- A passionate technologist with an inherent love for data, eager to drive insights and innovation
- Demonstrated mastery of SQL is essential, including proficiency in creating tables, views, stored procedures, and crafting succinct queries to populate Power BI models effectively.
- Hands-on experience in analysing and extracting data from diverse sources, showcasing a deep understanding of data extraction (including REST APIs) methodologies and best practices.
- Responsibilities:
- Lead the design and implementation of robust and scalable data architecture solutions on the Azure platform, ensuring optimal performance and efficiency.
- Drive the implementation of data integration processes to seamlessly ingest data from diverse sources into Azure SQL Server, leveraging Azure Data Factory to design and develop ETL processes efficiently.
- Champion the maintenance of data quality, reliability, and integrity within Azure-stored datasets by enforcing data governance policies, conducting QA checks, and establishing effective monitoring mechanisms to uphold data quality standards.
- Utilize analytical skills to thoroughly review API documentation and analyze raw data and source system data models, ensuring comprehensive understanding and preparation before loading data into the staging area.
- Take ownership of maintaining documentation such as data dictionaries and data models, and actively share knowledge and expertise with team members to cultivate a culture of continuous learning and improvement.
- Collaborate with Senior Data Analysts to assist with complex SQL queries and ensure seamless reporting in Power BI. Act as a backup during their absence to maintain reporting continuity and meet requirements.
- Demonstrate adaptability and effectiveness in working under a hybrid working model, delivering high-quality work across global teams with efficiency and professionalism.
- Strong communication and presentation skills to convey technical concepts to non-technical stakeholders and build collaboration across teams.
Skills and experience required:
- Extensive Data Warehouse Experience: including hands-on experience designing, building, and managing data warehouses using the Kimball methodology.
- Proficiency in Azure Tools: Demonstrated expertise in Azure Data Factory (ETL processes), Azure SQL Server, Azure DevOps, Key Vaults, and Logic Apps.
- Strong Data Modeling Skills: Proven ability to design efficient and scalable data warehouse architectures, including the creation of robust staging and production layers.
- Performance Optimization: Experience in optimizing data loads to ensure reliability, scalability, and high performance, with a focus on reducing processing times and improving efficiency.
- Forward-Thinking Vision: A solid understanding of advanced data technologies and practices, with the ability to scale the data warehouse to support future growth and evolving business needs.
- Integration Expertise: Experience integrating data from diverse sources, ensuring data accuracy and consistency throughout the ETL process.
- Problem-Solving Abilities: Adept at troubleshooting and resolving complex data pipeline and infrastructure issues.
- Collaboration Skills: Ability to work closely with data analysts, stakeholders, and cross-functional teams to align data solutions with business objectives.
- Agile and DevOps Practices: Familiarity with CI/CD pipelines and agile workflows to streamline data warehouse development and deployment
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