Gazelle Global
Technical Lead - Data Engineering
London
Posted 1 day ago
How your CV stacks up
1Upload CV
2Analyse CV
3Improve CV
Upload your CV to see how well it fits this job role
?%
About the Company
The Role
Technical Lead - Data Engineering
You will play a critical role in driving our enterprise data platform strategy.
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 GitHub Actions, Azure DevOps, 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 DevOps and DataOps 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 (IaC) 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.
Reasons to use Rodeo
Start with a chat, not a search bar
Grad scheme, placement, apprenticeship? Not sure what you want yet — that's fine. Your agent talks it through with you and turns "I have no idea" into a shortlist.
It searches the market for you
Every day your agent scans the market matching roles against what actually matters to you, not just keywords on a CV.
Only hits
No noise. No "maybe this fits." Just roles with a clear explanation of why they're right — and where to focus when applying.
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
Python & Data Engineering
- 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 & DevOps
- Strong experience designing and implementing CI/CD pipelines using GitHub Actions, Azure DevOps, Jenkins, GitLab CI/CD, or similar platforms.
- Experience implementing automated testing, code quality checks, release management, and deployment automation.
- Strong understanding of DevOps, DataOps, CI/CD best practices, and release governance.
Cloud & Platform Engineering
- 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.
Get help with your application
Your very own career expert that helps elevate your application to the next level.
Data Architecture
- 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.
Version Control & Engineering Practices
- Strong Git/GitHub 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, MicroStrategy, or other BI tools.
- Knowledge of Kubernetes, Docker, and containerized deployments.
- Experience with Databricks and modern lakehouse architectures.
- Azure Data Factory, Synapse Analytics, or AWS Glue experience.
- Experience implementing DataOps frameworks and observability platforms.
- Exposure to enterprise architecture and governance frameworks.
Trusted by 25,000+ job seekers
“It took my CV and asked me questions relevant to understanding what kind of jobs to suggest for me. Suggestions were almost perfect. Jobs were exactly what I’ve been looking for.”
Jessica, London
Skills
Python
Snowflake
DBT
Airflow
Azure
AWS
CI/CD
Terraform
Terragrunt
ETL/ELT
Data Architecture
SQL
DevOps
DataOps
Infrastructure as Code
Data Modeling
Location