Data Engineering Lead

Data Engineering Lead

Job Description

Data Engineering Lead.

Our ideal candidates should be passionate about the insurance Data & AI industry and have a deep understanding of the industry.

If you're a dynamic Data Engineering Lead who excels in a collaborative team environment and enjoys working with talented individuals, this could be the perfect opportunity for you.

Role & Responsibilities

• Possess around 15 years of work experience as at a reputable Data & AI services firm.

• Lead enterprise-scale data solutions using modern cloud data platforms, establishing robust data engineering practices that deliver scalable, governed data products for analytics and business intelligence.

• Design and implement Data Vault 2.0 methodologies on Snowflake to create agile, auditable enterprise data warehouses that support historical tracking, parallel development, and business-driven data modelling across multiple source systems.

• Drive transformation pipeline development using DBT to build maintainable, version-controlled data transformation logic with automated testing, documentation, and deployment workflows that ensure data quality and lineage transparency.

• Optimise Snowflake platform performance by designing virtual warehouse strategies, implementing materialised views, establishing role-based access controls, and managing compute resources to balance query performance with cost efficiency.

• Proficiency in Python for building custom data processing frameworks, implementing complex business logic beyond SQL capabilities, and integrating with APIs for data ingestion from diverse source systems.

• Stakeholder Engagement: Collaborate with key stakeholders across the client’s enterprise to identify business challenges, define requirements, and recommend process improvements. Act as a bridge between technical teams and business units to ensure alignment on project goals.

• Relationships: Foster strong relationships with key business stakeholders, including project managers, IT teams, and business partners, to ensure alignment of data and AI initiatives with organisational goals.

• Cloud platform certifications such as Snowflake SnowPro Core/Advanced Architect, Microsoft Certified: Azure Data Engineer Associate

You Must Possess

• Possess a bachelor’s or master’s degree.

• Knowledge of DataOps practices including CI/CD pipeline implementation for data workflows, automated testing frameworks for data quality validation, and GitOps approaches for infrastructure-as-code deployment.

• Strong Communication Skills: Ability to effectively communicate complex data insights and industry-specific concepts to both technical and non-technical stakeholders, with a flair for compelling storytelling.

• Drive meaningful customer conversations and achieve positive business outcomes.

• Engage with clients effectively, build strong business networks, and play a key role in achieving successful outcomes for clients.

• Maintains an active learning approach, staying current with industry trends, and applying these insights to develop solutions, initiate new projects, and shape capability roadmaps.

• Client office two days a week.