SOFTNICE UK LIMITED
Technical Lead - Data Engineering
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Technical Lead - Data Engineering
Role Overview
You will 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 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.
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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.
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.
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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.
Desirable Skills / Knowledge / 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 Monitor
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