Azure​/Databricks Data Engineer

Job Overview

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The Cloud Data Platforms team is part of the Insights and Data Global Practice and has seen strong growth and continued success across a variety of projects and sectors. Cloud Data Platforms is the home of the Data Engineers, Platform Engineers, Solutions Architects and Business Analysts who are focused on driving our customers digital and data transformation journey using the modern cloud platforms.

We specialise on using the latest frameworks, reference architectures and technologies using AWS, Azure and GCP.

As a Databricks Data Engineer with an Azure focus, you will be an integral part of our team dedicated to building scalable and secure data platforms. You will leverage your expertise in Databricks, Apache Spark, and Azure to design, develop, and implement data warehouses, data lake houses, and AI/ML models that fuel our data-driven operations.

Hybrid working:
The places that you work from day to day will vary according to your role, your needs, and those of the business; it will be a blend of Company offices, client sites, and your home; noting that you will be unable to work at home 100% of the time.

If you are successfully offered this position, you will go through a series of pre-employment checks, including: identity, nationality (single or dual) or immigration status, employment history going back 3 continuous years, and unspent criminal record check (known as Disclosure and Barring Service).

• Design and build high-performance data pipelines:
  Utilize Databricks and Apache Spark to extract, transform, and load data into Azure Data Lake Storage and other Azure services.
• Develop and maintain secure data warehouses and data lake houses:
  Implement data models, data quality checks, and governance practices to ensure reliable and accurate data.
• Build and deploy AI/ML models:
  Integrate Machine Learning into data pipelines, leverage Databricks ML and Azure ML to develop predictive models and drive business insights.
• Monitor and optimize data pipelines and infrastructure:
  Analyze performance metrics, identify bottlenecks, and implement optimizations for efficiency and scalability.
• Collaborate with cross-functional teams:
  Work closely with business analysts, data scientists, and Dev Ops engineers to ensure successful data platform implementations.
• Stay ahead of the curve:
  Continuously learn and adapt to the evolving landscape of big data technologies and best practices with a focus on how AI can support you in your delivery work.
• Minimum 10+ years of experience as a Data Engineer or similar role.
• Proven expertise in Databricks, Apache Spark, and data pipeline development and strong understanding of data warehousing concepts and practices.
• Experience with Microsoft Azure cloud platform, including Azure Data Lake Storage, Databricks and Azure Data Factory.
• Excellent problem-solving and analytical skills and strong communication and teamwork skills.
• Azure Data Engineer Associate and Databricks Certified Data Engineer Professional.

To be successfully appointed to this role, it is a requirement to obtain Security Check (SC) clearance.

To obtain SC clearance, the successful applicant must have resided continuously within the United Kingdom for the last 5 years, along with other criteria and requirements.

Throughout the recruitment process, you will be asked questions about your security clearance eligibility such as, but not limited to, country of residence and nationality.

Some posts are restricted to sole UK Nationals for security reasons; therefore, you may be asked about your citizenship in the application process.

You’ll be joining an accredited Great Place to work for Wellbeing in 2023. Employee wellbeing is vitally important to us as an organisation. We see a healthy and happy workforce a critical component for us to achieve our organisational ambitions. To help support wellbeing we have trained ‘Mental Health Champions’ across each of our business areas, and we have invested in wellbeing apps such as Thrive and Peppy.

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