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- Tasks: Lead the design and implementation of scalable data architecture solutions on Azure.
- Company: Join a forward-thinking company focused on data-driven insights and innovation.
- Benefits: Enjoy a fully remote position with a permanent full-time role.
- Why this job: Be part of a collaborative team driving impactful data solutions and analytics.
- Qualifications: Must have extensive experience in data warehousing, Azure tools, and SQL.
- Other info: Opportunity to work with global teams and enhance your technical skills.
The predicted salary is between 48000 - 84000 £ per year.
Are you an experienced data engineer with a strong skill set including Azure, SQL, ADF, ETL, REST API, and proven DWH development experience?
We’re supporting a client in their search for a senior data engineer to systematically source internal data to drive reporting and analytics internally for the business.
Note this is a permanent full-time position working directly for our client 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 analyzing and extracting data from diverse sources, showcasing a deep understanding of data extraction methodologies and best practices.
Scope:
The Senior Data Engineer will play a crucial role within the Data & Analytics team, driving the development and implementation of a centralized Data Warehouse infrastructure. This position involves architecting, designing, and delivering scalable data solutions to streamline and optimize data storage, integration, and management processes. Leveraging expertise in the Kimball Methodology and Azure Data Factory, the Senior Data Engineer will ensure seamless integration of data from diverse sources, maintaining consistency, accuracy, and reliability.
In addition to these responsibilities, the Senior Data Engineer will design and develop robust KPI dashboards to meet the needs of various stakeholders. They will work closely with Senior Data Analysts to provide well-aggregated and curated datasets, ensuring readiness for reporting and analytics purposes. This collaborative approach is essential to deliver high-quality insights and support data-driven decision-making across the organization.
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.
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Senior Data Engineer employer: Pop Science
Contact Detail:
Pop Science Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Data Engineer
✨Tip Number 1
Make sure to showcase your hands-on experience with Azure Data Factory and SQL in your conversations. Highlight specific projects where you've successfully implemented ETL processes, as this will demonstrate your practical knowledge and problem-solving skills.
✨Tip Number 2
Familiarize yourself with the Kimball methodology and be ready to discuss how you've applied it in your previous roles. This will show that you not only understand the theory but also know how to implement it effectively in real-world scenarios.
✨Tip Number 3
Prepare to discuss your experience with data quality and governance. Be ready to share examples of how you've maintained data integrity and reliability in past projects, as this is crucial for the role.
✨Tip Number 4
Since this position involves collaboration with Senior Data Analysts, think of ways you've successfully worked in cross-functional teams. Highlight your communication skills and ability to convey technical concepts to non-technical stakeholders.
We think you need these skills to ace Senior Data Engineer
Some tips for your application 🫡
Highlight Relevant Experience: Make sure to emphasize your extensive experience with Azure, SQL, and ETL processes in your application. Provide specific examples of projects where you've successfully implemented data solutions or managed data warehouses using the Kimball methodology.
Showcase Technical Skills: Clearly outline your technical skills related to Azure Data Factory, SQL Server, and data modeling. Mention any relevant certifications or training that demonstrate your proficiency in these areas.
Demonstrate Problem-Solving Abilities: Include examples of how you've tackled complex data challenges in previous roles. Highlight your analytical skills and ability to optimize data loads and ensure data quality, as these are crucial for the Senior Data Engineer position.
Tailor Your Application: Customize your cover letter and CV to reflect the specific requirements mentioned in the job description. Use keywords from the listing, such as 'data governance', 'KPI dashboards', and 'collaboration with Senior Data Analysts' to align your application with what the company is looking for.
How to prepare for a job interview at Pop Science
✨Showcase Your Technical Skills
Be prepared to discuss your experience with Azure, SQL, and ETL processes in detail. Highlight specific projects where you implemented data solutions using these technologies, and be ready to answer technical questions that demonstrate your mastery of SQL and data warehousing.
✨Demonstrate Your Problem-Solving Abilities
Prepare examples of how you've tackled complex data challenges in the past. Discuss your approach to data integration and quality assurance, and how you ensured the reliability and accuracy of the data in your previous roles.
✨Emphasize Collaboration and Communication
Since this role involves working closely with Senior Data Analysts and other stakeholders, be ready to share experiences where you successfully collaborated on projects. Highlight your ability to communicate technical concepts to non-technical team members effectively.
✨Prepare for Behavioral Questions
Expect questions that assess your adaptability and effectiveness in a hybrid working model. Think of scenarios where you demonstrated flexibility and professionalism while working with global teams, and be ready to discuss how you maintain high-quality work under varying circumstances.
