At a Glance
- Tasks: Lead the design and delivery of modern data solutions using cutting-edge technologies.
- Company: Join a forward-thinking company driving enterprise data platform strategies.
- Benefits: Competitive salary, flexible work options, and opportunities for professional growth.
- Other info: Dynamic team environment with excellent career advancement opportunities.
- Why this job: Make a real impact by shaping scalable and secure data platforms.
- Qualifications: Proven experience in data engineering leadership and strong technical skills.
The predicted salary is between 63000 - 77000 £ per year.
The Role Technical Lead - Data Engineering and play a critical role in driving our enterprise data platform strategy.
You will lead the design, development, and delivery of modern data solutions using Snowflake, DBT, Azure/AWS, Python, Airflow, and CI/CD technologies.
This role combines deep technical expertise with leadership responsibilities, guiding engineering teams, defining best practices, and ensuring the successful delivery of scalable, secure, and high-performing data platforms.
Responsibilities
- Lead the design and implementation of scalable and secure data platforms using Snowflake, DBT, Airflow, Python, and Azure/AWS services.
- Define technical architecture, coding standards, engineering best practices, and development frameworks for the data engineering team.
- Drive the adoption of CI/CD pipelines using Git Hub Actions, Azure Dev Ops, Jenkins, or similar tools to automate build, test, deployment, and release management processes.
- Lead the development, optimization, and maintenance of complex ETL/ELT pipelines for large-scale data processing.
- Establish Dev Ops and Data Ops practices to improve deployment efficiency, reliability, and operational excellence.
- Mentor and coach data engineers through technical guidance, code reviews, architecture reviews, and knowledge-sharing sessions.
- Collaborate with enterprise architects and business stakeholders to translate business requirements into scalable technical solutions.
- Own platform reliability, monitoring, performance tuning, and troubleshooting of production data pipelines.
- Implement Infrastructure as Code (Ia C) using Terraform/Terragrunt to automate cloud resource provisioning.
- Drive data quality, governance, security, and compliance standards across the data ecosystem.
- Lead technical discussions, solution design workshops, and project planning activities.
- Evaluate emerging technologies and recommend innovative approaches to improve data engineering capabilities and delivery processes.
- Support Agile delivery and provide technical leadership throughout the project lifecycle.
Qualifications
- Proven experience as a Technical Lead, Lead Data Engineer, or similar leadership role.
- Experience leading distributed development teams and delivering large-scale data engineering projects.
- Strong stakeholder management and technical decision-making capabilities.
- Required Skills
- Expert-level proficiency in Python for data engineering, automation, orchestration, and application development.
- Strong experience developing scalable ETL/ELT frameworks using Python and SQL.
- Hands-on experience with DBT, Airflow, Snowflake, and cloud-native data services.
- CI/CD & Dev Ops
- Strong experience designing and implementing CI/CD pipelines using Git Hub Actions, Azure Dev Ops, Jenkins, Git Lab CI/CD, or similar platforms.
- Experience implementing automated testing, code quality checks, release management, and deployment automation.
- Strong understanding of Dev Ops, Data Ops, CI/CD best practices, and release governance.
- Extensive experience designing cloud-based data solutions on Azure and/or AWS.
- Strong knowledge of cloud security, networking, monitoring, and operational best practices.
- Experience with Infrastructure as Code using Terraform and Terragrunt.
- Expertise in Data Vault, dimensional modelling, data warehousing, and modern data platform architectures.
- Advanced SQL development and performance optimization skills.
- Experience building enterprise-grade data products and analytics platforms
- Strong Git/Git Hub experience, including branching strategies, pull requests, code reviews, and release processes.
- Experience implementing engineering standards, quality gates, and development best practices.
- Communication & Stakeholder Engagement
- Excellent communication and presentation skills.
- Ability to engage with business and technical stakeholders at all levels.
- Strong problem-solving, analytical thinking, and decision-making capabilities.
- Preferred Skills
- Experience with Generative AI and AI-powered data engineering solutions.
- Experience with Power BI, Micro Strategy, or other BI tools.
- Knowledge of Kubernetes, Docker, and containerized deployments.
- Experience with Databricks and modern lakehouse architectures.
- Experience implementing Data Ops frameworks and observability platforms.
- Exposure to enterprise architecture and governance frameworks.
- #J-18808-Ljbffr
Technical Lead - Data Engineering employer: Gazelle Global
Join a leading organisation at the forefront of cyber security transformation in London, where you will play a pivotal role in delivering critical initiatives. Our collaborative work culture fosters innovation and growth, offering ample opportunities for professional development and advancement within a dynamic environment. With competitive rates and a commitment to employee well-being, we ensure that our team members thrive both personally and professionally.
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We think this is how you could land Technical Lead - Data Engineering
✨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 Gazelle Global!
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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 Gazelle Global.
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We think you need these skills to ace Technical Lead - Data Engineering
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 Gazelle Global, 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 Gazelle Global. 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 Gazelle Global
✨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 Gazelle Global!
✨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.
