Data Engineering Specialist

Aviva
Bristol
2 weeks ago
Create job alert

Data Engineering Specialist

Salary: Up to £65,000

A bit about the job: 

The Lead Data Engineer will be critical in ensuring development standards are maintained while delivering solutions within time and budgetary targets. This position suits a highly organized and effective communicator who can engage with stakeholders at all levels. Responsibilities include understanding detailed technical requirements and deliverables across multiple projects, providing informed technical input into the preparation of solution designs, and proactively balancing involvement within projects as necessary while supporting and guiding the development team.

Key Responsibilities:

Develop ETL solutions on a project-by-project basis, ensuring they are performant, secure, and aligned with governance standards.

Mentor developers of varying experience levels, encouraging a collaborative and productive team environment.

Lead solutions for complex problems, ensuring that code meets high standards through detailed reviews.

Collaborate with collaborators at all levels to offer technical expertise and project mentorship.

Support the development team in requirement clarifications, solution design, low-level design, sprint planning, code deployments, and resolving project blockers and issues.

Provide support for production applications, including defect analysis and fixing, while serving as a point of contact for technical mentorship and support within the wider team.

Skills and experience we’re looking for:

Proven track record in technical consultancy involving ETL/ELT/Data Warehouse projects, showcasing hands-on delivery and leadership experience.

Expertise in mentoring Data Engineering teams and leading projects in an offshore/onshore resource environment.

Proficiency in using ETL applications, particularly the Informatica suite of products (PowerCenter, BDM, IDMC), and experience with Cloud Technologies, preferably AWS (e.g., AWS Glue).

Experience with various Database technologies (Postgres, Redshift, Oracle, Snowflake) and scripting languages such as Python and PySpark for data transfer/manipulation.

Ability to assimilate technical and business information and translate these into practical solutions, while positively challenging existing and proposed solutions.

What you’ll get for this role:

Our purpose - with you today, for a better tomorrow – is a promise we make to our colleagues too. And one of the ways we live up to that promise is by investing in you. We have so much to offer when it comes to being an Aviva colleague.

Starting salary up to £65,000 (depending on skills, experience, and qualifications).

Bonus opportunity 10% of annual salary - Actual amount depends on your performance and Aviva’s

Generous pension scheme - Aviva will contribute up to 14%, depending on what you put in

29 days holiday plus bank holidays, and you can choose to buy or sell up to 5 days

Make your money go further - Up to 40% discount on Aviva products, and other retailer discounts

Up to £1,200 of free Aviva shares per year through our Matching Share Plan and share in the success of Aviva with our Save As You Earn scheme

Brilliantly supportive policies including parental and carer’s leave

Flexible benefits to suit you, including sustainability options such as cycle to work

Make a difference, be part of our Aviva Communities and use your 3 paid volunteering days to help others

We take your wellbeing seriously with lots of support and tools

Take a look to learn more. Put a salary into this calculator to see what your total Aviva Reward could be.

Aviva is for everyone:

We’re inclusive and welcome everyone – we want applications from all backgrounds and experiences. Excited but not sure you tick every box? Even if you don’t, we would still encourage you to apply. We also consider all forms of flexible working, including part time and job shares.

We flex locations, hours and working patterns to suit our customers, business, and you. Most of our people are smart working – spending around 50% of their time in our offices every week - combining the benefits of flexibility, with time together with colleagues.

Related Jobs

View all jobs

Lead data Engineer - Financial Markets - Day rate

Senior Data Architect - Databricks

Senior Analyst & Data Specialist

Databricks Tech Lead

Data Engineer

Data Engineer

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.

Portfolio Projects That Get You Hired for Machine Learning Jobs (With Real GitHub Examples)

In today’s data-driven landscape, the field of machine learning (ML) is one of the most sought-after career paths. From startups to multinational enterprises, organisations are on the lookout for professionals who can develop and deploy ML models that drive impactful decisions. Whether you’re an aspiring data scientist, a seasoned researcher, or a machine learning engineer, one element can truly make your CV shine: a compelling portfolio. While your CV and cover letter detail your educational background and professional experiences, a portfolio reveals your practical know-how. The code you share, the projects you build, and your problem-solving process all help prospective employers ascertain if you’re the right fit for their team. But what kinds of portfolio projects stand out, and how can you showcase them effectively? This article provides the answers. We’ll look at: Why a machine learning portfolio is critical for impressing recruiters. How to select appropriate ML projects for your target roles. Inspirational GitHub examples that exemplify strong project structure and presentation. Tangible project ideas you can start immediately, from predictive modelling to computer vision. Best practices for showcasing your work on GitHub, personal websites, and beyond. Finally, we’ll share how you can leverage these projects to unlock opportunities—plus a handy link to upload your CV on Machine Learning Jobs when you’re ready to apply. Get ready to build a portfolio that underscores your skill set and positions you for the ML role you’ve been dreaming of!

Machine Learning Job Interview Warm‑Up: 30 Real Coding & System‑Design Questions

Machine learning is fuelling innovation across every industry, from healthcare to retail to financial services. As organisations look to harness large datasets and predictive algorithms to gain competitive advantages, the demand for skilled ML professionals continues to soar. Whether you’re aiming for a machine learning engineer role or a research scientist position, strong interview performance can open doors to dynamic projects and fulfilling careers. However, machine learning interviews differ from standard software engineering ones. Beyond coding proficiency, you’ll be tested on algorithms, mathematics, data manipulation, and applied problem-solving skills. Employers also expect you to discuss how to deploy models in production and maintain them effectively—touching on MLOps or advanced system design for scaling model inferences. In this guide, we’ve compiled 30 real coding & system‑design questions you might face in a machine learning job interview. From linear regression to distributed training strategies, these questions aim to test your depth of knowledge and practical know‑how. And if you’re ready to find your next ML opportunity in the UK, head to www.machinelearningjobs.co.uk—a prime location for the latest machine learning vacancies. Let’s dive in and gear up for success in your forthcoming interviews.

Negotiating Your Machine Learning Job Offer: Equity, Bonuses & Perks Explained

How to Secure a Compensation Package That Matches Your Technical Mastery and Strategic Influence in the UK’s ML Landscape Machine learning (ML) has rapidly shifted from an emerging discipline to a mission-critical function in modern enterprises. From optimising e-commerce recommendations to powering autonomous vehicles and driving innovation in healthcare, ML experts hold the keys to transformative outcomes. As a mid‑senior professional in this field, you’re not only crafting sophisticated algorithms; you’re often guiding strategic decisions about data pipelines, model deployment, and product direction. With such a powerful impact on business results, companies across the UK are going beyond standard salary structures to attract top ML talent. Negotiating a compensation package that truly reflects your value means looking beyond the numbers on your monthly payslip. In addition to a competitive base salary, you could be securing equity, performance-based bonuses, and perks that support your ongoing research, development, and growth. However, many mid‑senior ML professionals leave these additional benefits on the table—either because they’re unsure how to negotiate them or they simply underestimate their long-term worth. This guide explores every critical aspect of negotiating a machine learning job offer. Whether you’re joining an AI-focused start-up or a major tech player expanding its ML capabilities, understanding equity structures, bonus schemes, and strategic perks will help you lock in a package that matches your technical expertise and strategic influence. Let’s dive in.