National AI Awards 2025Discover AI's trailblazers! Join us to celebrate innovation and nominate industry leaders.

Nominate & Attend

Senior Data Engineer...

Verityv Ecosystems
London
4 weeks ago
Applications closed

Related Jobs

View all jobs

Senior Data Engineer

Senior Data Engineer

Senior Data Engineer

Senior Data Engineer (SQL Server / AWS)

Senior Data Engineer - Snowflake - £100,000 - London - Hybrid

Senior Data Engineer

Job Description Company Overview: Verityv is an
innovative fast-growing Fintech start-up based in London,
revolutionizing the way Non-traditional financial risks are
delivered to the market. We are dedicated to leveraging
cutting-edge machine learning and artificial intelligence
technologies to evolve our product into an agentic AI system that
seamlessly integrates into clients' systems, automating compliance
and portfolio risk analysis processes. Job Summary: We are seeking
a Senior Data Engineer with 3-5 years of experience in building and
maintaining robust data pipelines for our SaaS platform, ensuring
high-quality data is available for analysis and decision-making.
You will work closely with cross-functional teams to support
data-driven initiatives and contribute to the development of
innovative solutions. Responsibilities: Web Crawling and Data
Extraction: - Develop, deploy, and maintain web crawlers using
Python to extract data from websites and social media platforms. -
Ensure the scalability, reliability, and efficiency of web scraping
processes. Data Cleaning and Preprocessing: - Perform data
cleaning, standardization, and normalization to ensure data quality
and consistency. - Handle missing data, outliers, and
inconsistencies in large datasets. Data Analysis and Modeling: -
Analyze extracted data using advanced statistical and machine
learning models. - Collaborate with data scientists to implement
state-of-the-art models for predictive and prescriptive analytics.
Financial Data Expertise: - Leverage past experience in financial
data analysis to provide insights and support decision-making
processes. - Work with financial datasets to identify trends,
patterns, and anomalies. Data Pipeline Development: - Design and
maintain ETL (Extract, Transform, Load) pipelines to streamline
data workflows. - Integrate data from multiple sources and ensure
seamless data flow across systems. Collaboration and Communication:

  • Work closely with cross-functional teams, including data
    scientists, analysts, and business stakeholders. - Communicate
    findings and insights effectively through visualizations, reports,
    and presentations. Qualifications: - Bachelor’s or Master’s degree
    in Computer Science, Data Science, Engineering, or a related field.
  • 3-5 years of experience as a Data Engineer or in a similar role -
    Proficiency in Python for web crawling (e.g., using libraries like
    Scrapy, BeautifulSoup, or Selenium). - Strong knowledge of data
    cleaning, standardization, and normalization techniques -
    Experience with data analysis and modeling using libraries such as
    Pandas, NumPy, Scikit-learn, or TensorFlow. - Familiarity with SQL
    and database management systems (e.g., PostgreSQL, MySQL). -
    Experience with cloud platforms (e.g., AWS, Azure, GCP) and big
    data tools (e.g., Spark, Hadoop) is a plus. - Prior experience in
    financial data analysis is highly preferred. - Understanding
    financial datasets, metrics, and industry trends. Preferred
    Qualifications: - Experience with API integrations and working with
    RESTful APIs. - Knowledge of data visualization tools (e.g.,
    Tableau, Power BI, or Matplotlib/Seaborn). - Familiarity with
    version control systems (e.g., Git). - Experience with
    containerization tools (e.g., Docker, Kubernetes). - Past
    experiences working in Fintech, Financial Services or related
    industries. What We Offer: - Competitive salary and benefits
    package. - Opportunities for professional growth and development. -
    A collaborative and innovative work environment. - The chance to
    work on cutting-edge projects with a talented team. How to Apply:
    Please submit your resume, cover letter, and any relevant portfolio
    or GitHub links to . We are excited to hear from
    you!
National AI Awards 2025

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 Jobs UK 2025: 50 Companies Hiring Now

Bookmark this guide—refreshed every quarter—so you always know who’s really expanding their data‑science teams. Budgets for predictive analytics, GenAI pilots & real‑time decision engines keep climbing in 2025. The UK’s National AI Strategy, tax relief for R&D & a sharp rise in cloud adoption mean employers need applied scientists, ML engineers, experiment designers, causal‑inference specialists & analytics leaders—right now. Below you’ll find 50 organisations that have advertised UK‑based data‑science vacancies or announced head‑count growth during the past eight weeks. They’re grouped into five quick‑scan categories so you can jump straight to the kind of employer—& culture—that suits you. For every company you’ll see: Main UK hub Example live or recent vacancy Why it’s worth a look (tech stack, mission, culture) Search any employer on DataScience‑Jobs.co.uk to view current ads, or set up a free alert so fresh openings land straight in your inbox.

Return-to-Work Pathways: Relaunch Your Data Science Career with Returnships, Flexible & Hybrid Roles

Returning to work after an extended break can feel like stepping into a whole new world—especially in a dynamic field like data science. Whether you paused your career for parenting, caring responsibilities or another life chapter, the UK’s data science sector now offers a variety of return-to-work pathways. From structured returnships to flexible and hybrid roles, these programmes recognise the transferable skills and resilience you’ve gained and provide mentorship, upskilling and supportive networks to ease your transition back. In this guide, you’ll discover how to: Understand the current demand for data science talent in the UK Leverage your organisational, communication and analytical skills in data science roles Overcome common re-entry challenges with practical solutions Refresh your technical knowledge through targeted learning Access returnship and re-entry programmes tailored to data science Find roles that fit around family commitments—whether flexible, hybrid or full-time Balance your career relaunch with caring responsibilities Master applications, interviews and networking specific to data science Learn from inspiring returner success stories Get answers to common questions in our FAQ section Whether you aim to return as a data analyst, machine learning engineer, data visualisation specialist or data science manager, this article will map out the steps and resources you need to reignite your data science career.

LinkedIn Profile Checklist for Data Science Jobs: 10 Tweaks to Elevate Recruiter Engagement

Data science recruiters often sift through dozens of profiles to find candidates skilled in Python, machine learning, statistical modelling and data visualisation—sometimes before roles even open. A generic LinkedIn profile won’t suffice in this data-driven era. This step-by-step LinkedIn for data science jobs checklist outlines ten targeted tweaks to elevate recruiter engagement. Whether you’re an aspiring junior data scientist, a specialist in MLOps, or a seasoned analytics leader, these optimisations will sharpen your profile’s search relevance and demonstrate your analytical impact.