Solution Architect - GCP Data Modernisation

TEKsystems
Greater London
2 weeks ago
Create job alert

Solution Architect - GCP Data Modernisation

TEKsystems Global Services is part of Allegis Group, a leading services company. TEKsystems Global Services provides a continuum of services ranging from capacity solutions to full outsourcing for applications, infrastructure and learning solutions. As a services provider, we leverage our expertise, experience and IP to help our customers achieve their business value through technology solutions.

The Solution Architect (SA) – GCP and Data is a Presales professional, responsible for solution development in support of Google Cloud, Data Modernization and Artificial Intelligence engagements in collaboration with TEKsystems Global Services sales partners. A successful Solution Architect possesses a deep understanding of the business domain coupled with a broad technical expertise. Their strength lies in diverse experience across various technological roles, enabling them to:

  • Approach business problems from multiple perspectives
  • Effectively communicate technical concepts to non-technical stakeholders
  • Leverage a toolbox of proven design strategies, patterns, and holistic solution viewpoints
  • Ask insightful technical questions and consider relevant factors

The SA will be the primary driver for identifying, scoping, and creating solutions and proposals that encompass technical approach, estimates, implementation, team structure, pricing and contracts. The SA will bring thought leadership, current industry know-how and applied solutions to improve existing service capabilities, engagement and delivery challenges and any research and development activities.

Responsibilities

  • Lead and own pre-sales activities, including solution design, proposal development, pricing and client presentations and contractual activities.
  • Ensure solutions align with industry best practices, architectural principles, and adhere to relevant standards and regulations.
  • Understand business requirements and other inputs such as customer terms and conditions for the technology solution and identify and mitigate risks that could hinder the technology's ability to meet those needs.
  • Prioritize and advocate for addressing non-functional requirements such as usability, reliability, performance, supportability, and security.
  • Design and architect scalable, secure, and cost-effective data solutions using GCP services such as BigQuery, Dataflow, Dataproc, Dataprep, Composer, Data Fusion, Data Studio, Cloud SQL, Cloud Functions and Cloud Storage.
  • Leverage AI and machine learning technologies, such as TensorFlow, Vertex AI, and AutoML, to enhance data insights and drive business value.
  • Ensure Delivery team requirements are communicated and that IT/ Facilities requirements are collected.
  • Implement data modernization initiatives, including data migration, data warehousing, data lakes, and data governance frameworks to continue to maintain deep technical skills.
  • Conduct technical assessments, proofs-of-concept, and feasibility studies to validate proposed solutions.
  • Package capabilities and solution content for use in sales and marketing activities.
  • Prepare value proposition and competitive positioning statements.
  • Participate in RFx Responses.
  • Provide feedback to practice to develop, enhance, and package new capabilities.
  • Stay up to date with the latest trends, technologies, and best practices in data modernization and AI.
  • Develop strategy and lead activities in landing and expanding business within our GCP and Data practice alongside our GCP alliance partnership.
  • Participate in Advisory & Steering Meetings including GCP alliance partnership meetings.

Requirements

  • Hands-on experience in data modernization projects, including data migration, data integration, data warehousing, and data governance.
  • Experience working with enterprise clients across the UK and Mainland Europe.
  • Strong proficiency in designing and implementing solutions on the Google Cloud Platform.
  • Certifications such as Google Cloud Professional Data Engineer and/or Google Cloud Professional Architect.
  • Hands-on experience with GCP data services, including BigQuery, Dataflow, Dataproc, Dataprep, Composer, Data Fusion, Data Studio, Cloud SQL, Cloud Functions and Cloud Storage. Knowledge of AI and machine learning technologies, such as TensorFlow, Vertex AI, and AutoML.
  • Experience with using IDEs and experience with Python and PySpark.
  • Experience with data modeling, ETL/ELT processes, and data integration techniques.
  • Familiarity with agile methodologies, DevOps practices, and cloud-native application development.
  • Strong problem-solving, analytical, and critical thinking skills.
  • Strong business acumen with the ability to develop a business case, to gather business requirements, and translate them into application development requirements and project scope.
  • Excellent communication and presentation skills, with the ability to articulate complex technical concepts to both technical and non-technical audiences.
  • Proven experience in pre-sales activities, solution design, and client-facing engagements.
  • Work with Sales and Contract teams on Statements of Work to ensure the proposed solution is translated to contracts.
  • Collaborate with practices on continued evolution of service offerings, presales & go-to market collateral such as case studies, account profiling, client presentation design etc.
  • Turnover from Sales to Delivery ensuring that expectations, schedules and ramp up time frames are managed.
  • Ensure client expectations are clearly communicated to delivery (client environment, culture, key players, escalation points, roles and responsibilities, vision, issues, risks, objectives etc.).
  • Provide advisory and thought leadership support to clients.

Qualification & Education

  • A technical bachelor's degree (Computer Science, Information Technology/Systems).
  • Experience in information technology and/or IT professional services.
  • Experience in client-facing presales roles developing new business, with high energy and dynamic personality.
  • Prior experience in playing key development roles on GCP implementation projects.
  • Prior experience in engagement management, project management with full application development lifecycle using multiple methodologies (AGILE/SCRUM, RUP, Waterfall, etc.)
  • Prior experience developing project estimations, project planning, and scheduling.
  • Strong communication skills, both written and verbal, with the ability to effectively develop and maintain client relationships.
  • Strong drive to remain current with emerging trends, technologies, and best practices in data modernization, AI, and generative AI domains.
  • Ability to travel to client locations, as needed.

Seniority level

Mid-Senior level

Employment type

Full-time

Job function

Consulting

Industries

IT Services and IT Consulting and Professional Services

#J-18808-Ljbffr

Related Jobs

View all jobs

Solution Architect (Databricks)

Solution Architect

Solution Architect (SA)

Solution Architect (Outside IR35 Contract)

Solution Architect - GCP Data Modernisation

Senior Solution Architect

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.