Microsoft D365 CE Data Migration / Data Integration Architect/Lead

HCLTech
Sheffield
1 month ago
Applications closed

Related Jobs

View all jobs

Data Architect

D365 & Power Platform Solutions Architect - Remote UK Wide

Microsoft D365 & Power Platform Analyst

Senior Data Architect

MS Dynamics 365 Functional Consultant

Azure Data Engineer (Ref: 1011547)

HCLTech is seeking a Microsoft Dynamics 365 CE Data Migration / Data Integration Architect/Lead to join their award winning and growing team. This individual’s primary responsibility will be to demonstrate a clear approach to Migration and integration efforts within the project team. The candidate must be able to work closely with different personality types and skillsets, be detail-oriented, and be meticulously organised. In addition, success requires the candidate to be able to prioritize multiple demands in a fast-paced environment.


Requirements:

  • Bachelor's or Master's degree in Computer Science, Information Systems, or a related field.
  • Proven experience as a data architect or in a similar role.
  • Strong expertise in data modelling, database design, and data integration techniques.
  • Proficiency in database management systems (e.g., SQL Server, Oracle, MySQL, MongoDB).
  • Knowledge of data governance frameworks, data quality management, and data security.
  • Familiarity with cloud-based data platforms (e.g., AWS, Azure, Google Cloud).
  • Excellent analytical and problem-solving skills.
  • Strong communication and collaboration abilities.
  • Ability to work independently and manage multiple projects simultaneously.
  • Certifications in data management or data architecture (e.g., CDMP, DAMA) are a plus.


Responsibilities:


  • Data Strategy Development: Development: Collaborate with business stakeholders to define data strategy and align it with organizational goals. Develop a roadmap for data architecture and identify opportunities for data optimization and enhancement.
  • Data Modelling and Design: Design and develop conceptual, logical, and physical data models to meet business requirements. Ensure data models are aligned with industry standards, best practices, and data governance policies.
  • Data Integration: Define data integration strategies and implement data integration processes to consolidate and synchronize data from various sources. Develop and maintain data integration pipelines, ensuring data accuracy, consistency, and reliability.
  • Data Governance and Quality: Establish data governance frameworks, policies, and procedures to ensure data integrity, security, and compliance. Implement data quality control measures to identify and resolve data issues.
  • Database Management: Oversee the design, implementation, and management of databases, ensuring optimal performance, scalability, and reliability. Evaluate and recommend appropriate database technologies and tools.
  • Collaboration and Communication: Collaborate with cross-functional teams, including data analysts, business intelligence teams, and software developers, to understand data requirements and provide technical guidance. Communicate data architecture and design decisions effectively to stakeholders.
  • Emerging Technologies: Stay updated with emerging trends and technologies in data management, analytics, and cloud computing. Evaluate and recommend new technologies and tools that can enhance the organization's data capabilities.


Essential Functions

  • Assist the Technical Architect in designing technical solutions to meet customer requirements in D365 CE.
  • Assist the Technical Architect in designing integrations between D365 applications and legacy/third party systems using multiple technologies, including Azure Logic Apps, Power Apps, Azure Data Factory, Fabric and SSIS.
  • Take part in, and in some cases lead, workshops with the customer to gather technical requirements with a view of ensuring technical solutions meet the customers’ requirements within the guidelines of the technical solution set out by the Technical Architect.
  • Report to the Technical Architect and/or Project Manager on a regular basis with updates on progress, risks/challenges and resourcing requirements.
  • Write Technical Design Documents detailing how technical solutions should be built so development teams can carry out the builds.
  • Write Integration Design Documents detailing how integration solutions should be built so development teams can carry out the builds.
  • Lead the development team, deciding on priorities for delivery and managing resources to deliver solutions in a timely manner to support the project
  • Be responsible for Quality Assurance of developments delivered by the development team, carrying out code reviews and best practice checks and ensuring quality delivery
  • Aid with regular quality audits for Implementation Programmes related to D365 CE
  • Assist the REM team with deployment of releases to customer environments
  • Manage development resources during SIT/SAT and UAT cycles to ensure proper levels of support including managing priorities and workloads of the team
  • Attend regular meetings with the Leads of all technical teams on the project to ensure all teams are working towards a singular goal
  • Mentor members of the development team to improve their skills
  • Contribute to Best Practice processes

Required Skills and Experience

  • Proficient/Skilled at PowerShell development
  • Proficient/skilled in Dev Ops ALM components/Release process
  • Proficient/Skilled at Azure Logic App Development
  • Proficient/Skilled in Azure components such as Azure Key Vault, On-Premise Data Gateway, Azure Monitor
  • Proficient/Skilled at Power Apps/DataVerse Development
  • Proficient/Skilled at SQL scripting/development.
  • Detailed understanding of security design principles for both D365 CE and Azure components, including the mechanisms for authorisation and interaction with these components.
  • Skilled at writing detailed technical documentation in a clear and concise manner.
  • A detailed knowledge of DevOps/Git and general rules/processes for development/source controls.
  • Great communication skills to enable clear and consistent communications with both members of the Technical team and also with Functional Consultants and customers’ staff
  • Good leadership skills: must be able to lead a team, manage timelines and priorities, and take responsibility for deliverables.

HCL Technologies is an Equal Opportunity Employer. Applicants receive consideration for employment regardless of their race, color, creed, religion, national origin, sex, sexual orientation, disability, age, marital status, or status with regard to public assistance.

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.

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.

Data Science Leadership for Managers: Strategies to Motivate, Mentor, and Set Realistic Goals in Data-Driven Teams

Data science has become a linchpin in modern business, transforming oceans of raw data into actionable insights that guide strategy, product development, and personalised customer experiences. With this surge in data-centric operations, the need for effective data science leadership has never been more critical. Guiding a team of data scientists, analysts, and machine learning engineers requires not only technical acumen but also the ability to foster collaboration, champion ethical practices, and align complex modelling efforts with overarching business goals. This article provides practical guidance for managers and aspiring leaders aiming to excel in data-driven environments. By exploring strategies to motivate data science professionals, develop mentoring frameworks, and set achievable milestones, you will be better prepared to steer your team towards meaningful, evidence-based outcomes.