Data Engineering Lead with Snowflake

Hi, we're glad you're here! We are hiring to our Aviva Services Excellence Centre! Take a look at our job description - maybe it suits you or one of your friends? 

As a Leading Data Engineer you will play a pivotal role in shaping and delivering the Financial Data Hub platform.

What will you be doing?

• Leading a team of Snowflake Data Engineers delivering analytical and operational use cases.

• Making strategic and tactical engineering decisions with long‑term impact.

• Ensuring platform alignment with enterprise architecture and organisational standards.

• Building scalable, secure, reliable engineering solutions with a strong focus on automation.

• Collaborating with Product Managers, BAs, Architects to align technical delivery with business needs.

• Owning CI/CD pipelines, platform maintenance, data security posture, and compliance with Aviva Controls.

• Providing daily leadership, coaching, mentoring and oversight of other team members.

• Driving continuous improvement, standardisation, and engineering best practices across the platform.

What we’re looking for?

• Deep hands‑on experience with Snowflake, including advanced capabilities such as Dynamic Tables, Snowpipe Streaming, Cortex AI, data sharing, replication, secure views, masking policies, row access policies, tags, streams, tasks, external tables, time‑travel, clone, stages, and storage integrations.

• Proficiency in Snowflake scripting (stored procedures in Python/SQL, UDFs, CTEs, window functions).

• Experience designing reusable frameworks, UDFs, and components using Snowpark or SQL.

• Good understanding of reliability patterns and performance optimisation for large‑scale data workloads.

• Proficiency in Python, SQL, and Airflow for orchestration and scheduling.

• Experience with ETL/ELT development, automation, and monitoring frameworks.

• Strong understanding of data modelling, data structures, and DBMS platforms (Redshift, Postgres, etc.).

• Experience implementing data quality rules, validation frameworks, and robust testing approaches.

• Familiarity with Git (branching, cloning, pull requests, conflict resolution, code reviews).

• Understanding of SDLC, CI/CD, and modern engineering practices, including Azure DevOps pipelines, agents, and repos.

• Knowledge of data formats such as Parquet, JSON, and YAML.

• Experience integrating data pipelines with cloud services and storage layers.

Nice to have:

• Hands‑on experience with dbt (models, macros, Jinja scripts, hooks, automated tests, snapshots, and dbt packages).

• Strong expertise in AWS, cloud‑native architectures, and serverless/data‑pipeline design and cloud cost optimisation approaches (AWS Glue experience is preferred).