At a Glance
- Tasks: Design and develop data pipelines, automate processes, and support data quality.
- Company: Join Apollo, a diverse and innovative team in the insurance sector.
- Benefits: Enjoy 31 days of leave, private medical insurance, and a flexible working environment.
- Other info: Embrace hybrid working and be part of a supportive, inclusive culture.
- Why this job: Make a real impact by shaping data solutions and driving innovation.
- Qualifications: Experience in data engineering, Azure tools, and strong communication skills.
Overview Data and Application Engineer role at Apollo. Your Role As a Data and Application Engineer, you will be working closely with colleagues across the business to deliver the data, applications, and services they need. This hands-on role will see you design and develop data pipelines, model and transform data for ease of use, and automate key business processes. You will also play a vital role in supporting data quality, timeliness, and governance, ensuring Apollo’s data strategy continues to evolve and thrive. What you will do Build strong relationships with stakeholders to understand requirements and shape effective data solutions. Design and implement data models and ETL pipelines aligned with our data platform principles. Develop, maintain, and enhance applications and automation tools that support business operations. Act as a subject matter expert in Azure Data Factory, Azure Databricks, Unity Catalogue, and SQL Server. Apply best practice to data quality, lineage, and governance, ensuring compliance and security standards are met. Contribute to agile delivery processes, code control, and quality assurance standards. Monitor, troubleshoot, and improve existing data sets and processes, identifying opportunities to enhance coverage and performance. Support colleagues through testing, training, and knowledge transfer, enabling them to fully utilise data solutions. What we are looking for Proven experience in data engineering and solution design. Strong technical expertise in Azure Data Factory, Azure Databricks, Unity Catalogue, and SQL Server. Practical knowledge of data modelling and ETL pipeline development. Ability to profile and analyse raw data, operational systems, and business processes. Hands-on coding and development skills, with a focus on quality, testing, and standards. Strong communication and stakeholder engagement skills, with the ability to explain complex solutions clearly. A collaborative, problem-solving mindset with a focus on continuous improvement and innovation. What you will get in return Our compensation package is designed to attract top talent. In addition to a fair and attractive salary, this role offers a discretionary bonus and a comprehensive range of benefits, including 31 days of annual leave, a non-contributory pension and private medical insurance. Our Commitment to Inclusion Apollo is a growing and diverse team of empowered and passionate experts who focus on bringing innovation, data driven decision making and collaboration to every relationship and every risk. To meet the needs of a demanding global insurance market, we need a diverse workforce that truly understands the international communities we serve. That is why we're focused on developing diverse talent at every level; inclusion and diversity means more to us than just chasing a target and we are committed to supporting and celebrating difference. Our people are at the heart of our business which is why we value the diversity of thought and talent of every member of our team. We offer a range of support and run a programme of events and training that recognise the challenges and opportunities relating to diversity. Hybrid
Data and Application Engineer employer: Apollo
Apollo, a Skyward Group company, is an exceptional employer that champions innovation and collaboration within the dynamic environment of Lloyd's of London. With a commitment to employee growth, we offer a competitive salary, comprehensive benefits, and a culture that values diversity and inclusion, ensuring every team member feels empowered and supported. Our flexible working arrangements and focus on mentorship create a rewarding atmosphere where actuaries can thrive and contribute to meaningful projects in the insurance sector.
StudySmarter Expert Advice🤫
We think this is how you could land Data and Application Engineer
✨Get Involved in Data Science Meetups
Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like Apollo!
✨Show Off Your Projects
Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Data and Application Engineer at Apollo.
✨Leverage Professional Networks
Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like Apollo.
✨Apply Directly through Our Website
When you find a suitable opening like Data and Application Engineer at Apollo, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at Apollo, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Apollo. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Apollo
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Apollo!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
