Senior Data Engineer (DBT and Databricks/Snowflake)

Overview

Responsibilities

• Design, build, and maintain scalable data pipelines and transformation workflows using Databricks or Snowflake in combination with dbt.
• Ensure high performance, reliability, and strong engineering standards across the data platform.
• Lead solution design efforts, contributing to architecture across ingestion, storage, modelling, and consumption layers.
• Implement modern data engineering patterns such as ELT, medallion architecture, and CI/CD-enabled development.
• Configure and optimise platform components including clusters, warehouses, permissions, and governance frameworks.
• Collaborate closely with cloud, analytics, and data science teams to deliver robust, production-ready solutions.
• Manage vendor relationships, supporting data quality and lineage frameworks, automating testing and monitoring, and driving continuous improvement through code reviews, engineering best practices, and mentorship of junior team members.

Experience & Qualifications

• Strong hands-on experience with Databricks (PySpark / Spark SQL) or Snowflake.
• Proficiency with dbt Core or dbt Cloud, including model development, testing, documentation, and deployment.
• Strong SQL development expertise, with experience working on complex transformations and performance tuning.
• Experience with cloud platforms (Azure, AWS, or GCP).
• Hands-on experience with version control (Git), CI/CD, and workflow orchestration tools (Airflow, Azure Data Factory, etc.).
• Understanding of medallion architecture, ELT patterns, and modular data modelling.
• Strong analytical and problem-solving capability.
• Excellent communication and strong stakeholder management skills.
• Proven ability to lead initiatives, work independently, and support decision-making across data projects.