Queen Square Recruitment
Technical Lead- Data Engineering
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New Exciting Opportunity for the Role of Technical Lead - Data Engineering
Location: London (Hybrid- 2 days in office)
Contract Duration: 6 months
IR35 Status: Inside IR35
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.
Essential Skills
Technical Leadership
- 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.
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.
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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.
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.
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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.
Desirable Skills / Experience
- 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.
Languages: Python (primary), SQL, Bash
Cloud: Azure, AWS
Tools: Airflow, DBT
Data: Snowflake, Delta Lake, Redis, Azure Data Lake
Infra & Ops: Terraform, GitHub Actions, Azure DevOps, Azure Monito
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