Project People | Data Warehouse Manager

Project People
Reading
2 months ago
Applications closed

Related Jobs

View all jobs

Enterprise Risk Manager

Project Manager

People Systems and MI Manager

Risk Controller / Project Controller

Business Applications Analyst & Project Manager

Senior Automation Project Manager

Data Warehouse Manager


Considering applying for this job Do not delay, scroll down and make your application as soon as possible to avoid missing out.

Permanent

Theale/ Hybrid – 2-3 days per week onsite

Main purpose of the role

You will be leading and supporting the Data Warehouse team in production of BAU data loads, storage, DR, reporting and outbound data. Be the authority and give guidance on database management, development, architecture, future design considerations, performance improvements and monitoring.

You will develop and apply best practice in above areas creating and delivering a roadmap for data warehouse future.

You will be working closely in collaboration with teams across the company and its third-party suppliers to ensure the efficient operation of the strategic information services and the delivery of the overall BI Team roadmap and project developments.

Key Responsibilities

Team and task management

  • Lead the data warehouse team, managing workload and expectations to the business. Developing /managing team and pipeline of work to deliver all aspects of issues, reporting and development in a timely fashion.
  • Work with team to build objectives and plan in line with BI roadmap. Lead, develop and mentor a forward-looking customer centric Data Warehouse Team
  • Work with the business and the rest of the BI team to understand future requirements and plan accordingly.
  • Represent and promote interests of data warehouse team across the business through appropriate meetings around BAU and projects.

Delivery

  • Manage and assist with BAU work and report production including review and continual development of the daily and overall warehouse processes/controls to improve the performance and reliability of the system.
  • Lead and manage team to operate in and across specialist functions such as Data Engineering
  • Work with team to deliver best practice database design to deliver the requirements of the business
  • Manage and assist in integration of new data sources into the data warehouse in a timely fashion to allow reporting and data storage.
  • Drive the Data Warehouse team to deliver the solutions that fulfil the Business information needs and align with the Data strategy and vision.
  • Monitor Azure costs and proactively look for ways of optimizing the data warehouse to reduce spend.
  • Be authority on database architecture and design for current and future development.
  • Implement and maintain access to data warehouse and databases using Role Based Access Controls (RBAC) principles.

Experience Required:

  • Team leadership and development
  • MSSQL/ MS SQL Azure
  • Database architecture and design including pros and cons of relevant schemas/structure etc
  • All aspects of MSSQL stack: SSIS, SSRS, SSMS etc
  • Database Installation, configuration, maintenance, monitoring, backups and recoveries
  • Stakeholder management
  • Bulk Copy Programme
  • SQL Profiler

Desirable

  • Telecoms Background
  • Project Manager experience
  • Scripting Languages – Powershell, Javascript, JQuery,VBScript,BatchScript
  • Azure DevOps

Get the latest insights and jobs direct. Sign up for our newsletter.

By subscribing you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Tips for Staying Inspired: How Data Science Pros Fuel Creativity and Innovation

Data science sits at the dynamic intersection of statistics, computer science, and domain expertise, driving powerful innovations in industries ranging from healthcare to finance, and from retail to robotics. Yet, the daily reality for many data scientists can be a far cry from starry-eyed talk of AI and machine learning transformations. Instead, it often involves endless data wrangling, model tuning, and scrutiny over metrics. Maintaining a sense of creativity in this environment can be an uphill battle. So, how do successful data scientists continue to dream big and innovate, even when dealing with the nitty-gritty of data pipelines, debugging code, or explaining results to stakeholders? Below, we outline ten practical strategies to help data analysts, machine learning engineers, and research scientists stay inspired and push their ideas further. Whether you’re just starting out or looking to reinvigorate a long-standing career, these pointers can help you find fresh sparks of motivation.

Top 10 Data Science Career Myths Debunked: Key Facts for Aspiring Professionals

Data science has become one of the most sought-after fields in the tech world, promising attractive salaries, cutting-edge projects, and the opportunity to shape decision-making in virtually every industry. From e-commerce recommendation engines to AI-powered medical diagnostics, data scientists are the force behind innovations that drive productivity and improve people’s lives. Yet, despite the demand and glamour often associated with this discipline, data science is also shrouded in misconceptions. Some believe you need a PhD in mathematics or statistics; others assume data science is exclusively about machine learning or coding. At DataScience-Jobs.co.uk, we’ve encountered a wide array of myths that can discourage talented individuals or mislead those exploring a data science career. This article aims to bust the top 10 data science career myths—providing clarity on what data scientists actually do and illuminating the true diversity and inclusiveness of this exciting field. Whether you’re a recent graduate, a professional looking to pivot, or simply curious about data science, read on to discover the reality behind the myths.

Global vs. Local: Comparing the UK Data Science Job Market to International Landscapes

How to evaluate salaries, opportunities, and work culture in data science across the UK, the US, Europe, and Asia Data science has proven to be more than a passing trend; it is now a foundational pillar of modern decision-making in virtually every industry—from healthcare and finance to retail and entertainment. As the volume of data grows exponentially, organisations urgently need professionals who can transform raw information into actionable insights. This high demand has sparked a wave of new opportunities for data scientists worldwide. In this article, we’ll compare the UK data science job market to those in the United States, Europe, and Asia. We’ll explore hiring trends, salary benchmarks, and cultural nuances to help you decide whether to focus your career locally or consider opportunities overseas or in fully remote roles. Whether you’re a fresh graduate looking for your first data science position, an experienced data professional pivoting from analytics, or a software engineer eager to break into machine learning, understanding the global data science landscape can be a game-changer. By the end of this overview, you’ll be better equipped to navigate the expanding world of data science—knowing which skills and certifications matter most, how salaries differ between regions, and what to expect from distinct work cultures. Let’s dive in.