The Data Platform Engineer is responsible for the implementation of data centric business deliverables – data manipulation, building data systems and data pipelines. It is expected that the Data Platform Engineer can contribute to data solution design as well articulate this back to the business with clarity. Designed and/or implemented business solutions will be considered fit for purpose on several levels notably: cost, requirement, resilience, performance, security and future proofing/improvements. The Engineer will collaborate with and support technology teams, data researchers, data analysts and data scientists on data initiatives and will ensure optimal data delivery architecture is consistent throughout ongoing projects. This person would also be key in the distribution of knowledge and skills around data manipulation and data flow services to the wider Technology team/members.
Key responsibilities
Data Solutions Implementation – Applying business-data logic to identify, design and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing.
Performance and Testing - Need to ensure that products in production perform as efficiently and effectively as possible. At the same time follow internal testing practices applying appropriate review strategies.
Continuous Learning - The Engineer is expected to always be up to date with industry standards and technological advancements that would improve the quality of product development, to apply the knowledge to enhance business continuity, performance, security and costs savings.
Creating best practices - Create, lead and contribute to creation of best practices and standards which must be followed when creating any business solutions that the team owns.
Monitoring and Support – Ensure any services that the team owns are always in best health, respond to incidents and propose solutions for improvements.
Training/Coaching - Spread the knowledge learned. Train and coach colleagues how to work with various products, services that the team owns and what standards and best practices to follow.
Documentation - Create required documentation to meet business objectives and compliance requirements.
Requirements
Skills/Proficiencies required
Technical skills/experiences:
- Skilled in SQL(T-SQL) programming
- Skilled in Data Processing and Integration Tools (ADF / SSIS)
- Skilled in Data Storage and Management Systems, Data Formats (RDBMS / NoSQL / JSON / XML)
- Skilled in working with Microsoft Azure Data Services
- Skilled in CI/CD Tools (preferably Azure DevOps)
- Skilled in writing infrastructure as code scripts (ARM Templates / PowerShell / Bash)
- Advanced programming skills
- Microsoft Azure Fundamentals certified
- Microsoft Azure Data Engineer Associate certified
- Experience in Agile methodologies
- Experience in – Business Intelligence tools (SSRS / PowerBI / Tableau)
- Advantageous - Microsoft Certified: Fabric Data Engineer Associate
- Advantageous - Experience in Microsoft Fabric
- Advantageous – degree in Computer science, IT or similar
- Advantageous – any other data engineering or Cloud platform certifications
Benefits
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