Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Snowflake Data Engineer

NTT America, Inc.
City of London
1 week ago
Applications closed

Related Jobs

View all jobs

Snowflake Specialist Data Engineer

Snowflake Data Engineer

Snowflake Data Engineer - AWS, Airflow & Iceberg

Senior Snowflake Data Engineer

Data Engineer - Snowflake

Data Engineer - Snowflake

The team you'll be working with:

We are seeking an accomplished and detail-oriented Snowflake Data Engineer to join our Data & AI practice. The successful candidate will bring deep expertise in data engineering, ETL/ELT pipelines, and cloud-native data platforms, with a strong focus on Snowflake. This role is critical in building and optimising modern data ecosystems that enable data-driven decision making, advanced analytics, and AI capabilities for our clients.

As a trusted practitioner, you will collaborate with architects, developers, and analysts to design, implement, and maintain secure and high-performing data pipelines. You will thrive in a collaborative, client-facing environment, with a passion for solving complex data challenges, driving innovation, and ensuring the seamless delivery of data solutions.

What you\'ll be doing:Primary Responsibilities:
  • Client Engagement & Delivery

  • Data Pipeline Development (Batch and Streaming)

  • Snowflake & Cloud Data Platforms

  • Data Architecture & Modelling

  • Collaboration & Best Practices

  • Quality, Governance & Security

Business Relationships:
  • Solution Architects

  • Data Engineers, Developers, ML Engineers and Analysts

  • Client stakeholders up to Head of Data Engineering, Chief Data Architect, and Analytics leadership

What experience you\'ll bring:Competencies / Critical Skills:
  • Proven experience in data engineering and pipeline development on Snowflake and cloud-native platforms.

  • Strong consulting values with ability to collaborate effectively in client-facing environments.

  • Hands-on expertise across the data lifecycle: ingestion, transformation, modelling, governance, and consumption.

  • Strong problem-solving, analytical, and communication skills.

  • Experience leading or mentoring teams of engineers to deliver high-quality scalable data solutions.

Technical Expertise:
  • Deep expertise with Snowflake features (warehouses, Snowpark, data sharing, performance tuning).

  • Proficiency in ETL/ELT tools such as DBT, Matillion, Talend, or equivalent.

  • Strong SQL and Python (or equivalent language) skills for data manipulation and automation.

  • Hands-on experience with cloud platforms (AWS, Azure, GCP).

  • Knowledge of data modelling methodologies (star schemas, Data Vault, Kimball, Inmon).

  • Familiarity with data lake architectures and distributed processing frameworks (e.g., Spark, Hadoop).

  • Experience with version control tools (GitHub, Bitbucket) and CI/CD pipelines.

  • Understanding of data governance, security, and compliance frameworks.

  • Exposure to AI/ML workloads desirable.

Experience, Qualifications, and Education:
  • Experience: Minimum 5–8 years in data engineering, data warehousing, or data architecture roles, with at least 3+ years working with Snowflake.

  • Education: University degree required.

  • Preferred: BSc/MSc in Computer Science, Data Engineering, or related field

  • Snowflake certifications (SnowPro Core, Advanced) highly desirable.

Measures of Success:
  • Delivery of high-performing, scalable, and secure data pipelines aligned to client requirements.

  • High client satisfaction and successful adoption of Snowflake-based solutions.

  • Demonstrated ability to innovate and improve data engineering practices.

  • Contribution to the growth of the practice through reusable assets, accelerators, and technical leadership.

Who we are:

We’re a business with a global reach that empowers local teams, and we undertake hugely exciting work that is genuinely changing the world. Our advanced portfolio of consulting, applications, business process, cloud, and infrastructure services will allow you to achieve great things by working with brilliant colleagues, and clients, on exciting projects.

Our inclusive work environment prioritises mutual respect, accountability, and continuous learning for all our people. This approach fosters collaboration, well-being, growth, and agility, leading to a more diverse, innovative, and competitive organisation. We are also proud to share that we have a range of Inclusion Networks such as: the Women’s Business Network, Cultural and Ethnicity Network, LGBTQ+ & Allies Network, Neurodiversity Network and the Parent Network.

For more information on Diversity, Equity and Inclusion please click here: Creating Inclusion Together at NTT DATA UK | NTT DATA (https://uk.nttdata.com/creating-inclusion-together)

What we\'ll offer you:

We offer a range of tailored benefits that support your physical, emotional, and financial wellbeing. Our Learning and Development team ensure that there are continuous growth and development opportunities for our people. We also offer the opportunity to have flexible work options.

You can find more information about NTT DATA UK & Ireland here: https://uk.nttdata.com/

We are an equal opportunities employer. We believe in the fair treatment of all our employees and commit to promoting equity and diversity in our employment practices. We are also a proud Disability Confident Committed Employer - we are committed to creating a diverse and inclusive workforce. We actively collaborate with individuals who have disabilities and long-term health conditions which have an effect on their ability to do normal daily activities, ensuring that barriers are eliminated when it comes to employment opportunities. In line with our commitment, we guarantee an interview to applicants who declare to us, during the application process, that they have a disability and meet the minimum requirements for the role. If you require any reasonable adjustments during the recruitment process, please let us know. Join us in building a truly diverse and empowered team.


#J-18808-Ljbffr

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

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

Industry Insights

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

Data Science Recruitment Trends 2025 (UK): What Job Seekers Need To Know About Today’s Hiring Process

Summary: UK data science hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise rigorous problem framing, high‑quality analytics & modelling, experiment/causality, production awareness (MLOps), governance/ethics, and measurable product or commercial impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for product/data scientists, applied ML scientists, decision scientists, econometricians, growth/marketing analysts, and ML‑adjacent data scientists supporting LLM/AI products. Who this is for: Product/decision/data scientists, applied ML scientists, econometrics & causal inference specialists, experimentation leads, analytics engineers crossing into DS, ML generalists with strong statistics, and data scientists collaborating with platform/MLOps teams in the UK.

Why Data Science Careers in the UK Are Becoming More Multidisciplinary

Data science once meant advanced statistics, machine learning models and coding in Python or R. In the UK today, it has become one of the most in-demand professions across sectors — from healthcare to finance, retail to government. But as the field matures, employers now expect more than technical modelling skills. Modern data science is multidisciplinary. It requires not just coding and algorithms, but also legal knowledge, ethical reasoning, psychological insight, linguistic clarity and human-centred design. Data scientists are expected to interpret, communicate and apply data responsibly, with awareness of law, human behaviour and accessibility. In this article, we’ll explore why data science careers in the UK are becoming more multidisciplinary, how these five disciplines intersect with data science, and what job-seekers & employers need to know to succeed in this transformed field.

Data Science Team Structures Explained: Who Does What in a Modern Data Science Department

Data science is one of the most in-demand, dynamic, and multidisciplinary areas in the UK tech and business landscape. Organisations from finance, retail, health, government, and beyond are using data to drive decisions, automate processes, personalise services, predict trends, detect fraud, and more. To do that well, companies don’t just need good data scientists; they need teams with clearly defined roles, responsibilities, workflows, collaboration, and governance. If you're aiming for a role in data science or recruiting for one, understanding the structure of a data science department—and who does what—can make all the difference. This article breaks down the key roles, how they interact across the lifecycle of a data science project, what skills and qualifications are typical in the UK, expected salary ranges, challenges, trends, and how to build or grow an effective team.