At a Glance
- Tasks: Lead data engineering solutions and mentor teams in a dynamic consultancy environment.
- Company: Join a top-tier digital consultancy driving impactful data transformation programmes.
- Benefits: Enjoy a six-figure salary, guaranteed bonus, flexible working, and comprehensive healthcare.
- Why this job: Be a key player in shaping data strategies while advancing your career in a high-growth setting.
- Qualifications: Extensive AWS experience and proven leadership in multi-million-pound projects required.
- Other info: This is a greenfield opportunity for a hands-on leader with a consulting mindset.
The predicted salary is between 63000 - 84000 £ per year.
Senior Data Engineer
Location: London (Hybrid)
Function: Data Engineering / Data Platform
Salary: Up to £140,000 base + bonus + benefits
About the Role
Our client is a global commodities and energy trading firm operating at the intersection of quantitative research, technology, and trading. Following the recent acquisition of a major energy trading and technology business, the firm has significantly expanded its capabilities in renewable power optimisation, analytics, and physical gas trading across international markets.
They are now hiring a Senior Data Engineer to join their Technology Data, AI & UX team in London.
This team sits close to the trading floor and is responsible for building the data infrastructure that supports traders, quantitative researchers, and data scientists. The work focuses on building scalable pipelines, enabling real-time analytics, and delivering high-quality datasets used for predictive modelling, machine learning, and systematic trading strategies.
This role requires someone who combines strong technical data engineering capability with commercial awareness, capable of working directly with front-office stakeholders and translating trading requirements into robust data solutions.
What You’ll Be Doing
- Building and maintaining high-performance data pipelines ingesting structured and unstructured datasets from a variety of internal and external sources.
- Developing ingestion processes including scrapers, ETL pipelines, crawlers, streaming jobs, and services.
- Cleaning, transforming, and enriching datasets to ensure high quality and usability across analytics and trading use cases.
- Designing storage solutions across data lakes, databases, and analytical warehouses.
- Delivering data internally via APIs, Python libraries, and direct database access.
- Maintaining and optimising existing pipelines and databases used by trading and analytics teams.
- Supporting data scientists and quantitative teams by enabling access to cloud resources, datasets, and internal Python tooling.
- Contributing to the automation of post-processing tasks including prediction pipelines and visualisation workflows.
- Collaborating directly with traders and front-office teams to develop data solutions for real-time analytics and trading decisions.
- Maintaining documentation and knowledge bases around data sources, architecture, and pipelines.
Ideal Background
The successful candidate will bring strong hands-on data engineering experience and the ability to operate in a front-office, commercially focused environment.
Core experience required:
- Strong Python development, particularly for data ingestion, crawling, parsing, and transformation.
- Extensive experience working with SQL and analytical databases, ideally including Amazon Redshift or similar time-series platforms.
- Experience building production data pipelines in AWS cloud environments.
- Familiarity with Docker containers and CI/CD pipelines.
- Experience with Infrastructure as Code and deployment tooling such as CloudFormation or CDK.
- Strong understanding of data pipeline design, performance optimisation, and data quality practices.
- Experience working directly with front-office stakeholders such as traders, quants, or analysts.
- Comfortable operating in agile, fast-paced engineering teams.
Highly desirable experience:
- Exposure to commodities, energy trading, or financial markets.
- Experience supporting real-time or near-real-time analytics environments.
- Knowledge of additional AWS services such as S3, Lambda, Athena, Kinesis, EMR, Fargate, or API Gateway.
- Experience with big data technologies including Spark, Databricks, Hadoop, or Dask.
- Familiarity with data visualisation tooling such as Plotly.
- Experience mentoring junior engineers or leading technical initiatives.
What You’ll Receive
- Base salary up to £140,000 depending on experience.
- Participation in a performance-based discretionary bonus scheme.
- 25 days annual leave plus public holidays.
- Comprehensive benefits including private medical, dental, life insurance, and strong pension contributions.
- Access to training and development programmes to support ongoing technical growth.
- The opportunity to work in a high-performing trading environment where technology directly impacts market decisions.
Who Should Apply
This role will suit a senior data engineer who enjoys operating close to the business, particularly in environments where data directly influences trading or commercial outcomes.
Candidates coming from financial services, trading firms, hedge funds, energy markets, or high-performance data platforms will likely transition most easily, though strong engineers from other real-time data environments will also be considered.
If you are looking to work on complex data challenges, collaborate with front-office teams, and build systems that power real-world trading decisions, this is a strong opportunity.
Senior Data Engineer employer: Anson McCade
Contact Detail:
Anson McCade Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Data Engineer
✨Tip Number 1
Network with professionals in the data engineering field, especially those with experience in AWS. Attend industry meetups or webinars to connect with potential colleagues and learn about their experiences, which can give you insights into the role and the company culture.
✨Tip Number 2
Familiarise yourself with the specific AWS services mentioned in the job description, such as S3, Glue, and Redshift. Consider building a small project or case study that showcases your ability to use these tools effectively, as this will demonstrate your hands-on experience during interviews.
✨Tip Number 3
Prepare to discuss your previous leadership experiences, particularly in managing large technical teams and engaging with senior stakeholders. Think of specific examples where you successfully led projects or initiatives, as this will be crucial for demonstrating your fit for a Principal Data Engineer role.
✨Tip Number 4
Stay updated on the latest trends in data engineering and cloud technologies. Being knowledgeable about emerging tools and methodologies will not only help you in interviews but also show your commitment to continuous learning and improvement in the field.
We think you need these skills to ace Senior Data Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your extensive hands-on experience in AWS data engineering environments. Focus on your leadership roles in multi-million-pound projects and your ability to engage with senior stakeholders.
Craft a Compelling Cover Letter: In your cover letter, emphasise your consulting mindset and how your technical expertise aligns with the company's needs. Mention specific AWS services you have worked with and any relevant certifications.
Showcase Relevant Projects: Include examples of enterprise-grade data engineering solutions you've led, particularly those involving cloud data lake architectures and ETL/ELT patterns. Highlight your role in shaping project strategies and mentoring teams.
Prepare for Technical Questions: Anticipate technical questions related to AWS services like S3, Glue, and Redshift. Be ready to discuss your experience with data pipeline automation and CI/CD processes, as well as your familiarity with data visualisation tools.
How to prepare for a job interview at Anson McCade
✨Showcase Your AWS Expertise
Make sure to highlight your extensive hands-on experience with AWS services like S3, Glue, and Redshift. Be prepared to discuss specific projects where you've successfully implemented these technologies, as this will demonstrate your capability to lead enterprise-grade data engineering solutions.
✨Engage with Stakeholders
Since the role involves significant stakeholder engagement, practice articulating how you've effectively communicated with senior client stakeholders in past projects. Share examples of how you’ve navigated complex discussions and built strong relationships at the CxO or Director level.
✨Demonstrate Leadership Skills
As a Principal Data Engineer, you'll be expected to mentor large technical teams. Prepare to discuss your leadership style and provide examples of how you've guided teams through challenging projects, ensuring successful delivery and fostering a collaborative environment.
✨Prepare for Technical Challenges
Expect to face technical questions related to data pipeline automation, ETL/ELT patterns, and cloud data lake architectures. Brush up on these topics and be ready to solve hypothetical problems or case studies that may arise during the interview.