Senior Data Engineer

• Develop and maintain scalable data pipelines to support operational and analytical needs.

• Collaborate with data scientists, analysts, and business teams to understand data requirements

and deliver solutions that align with organizational goals.

• Optimize and maintain cloud -based data infrastructure (e.g., Snowflake, Azure) for performance

and cost -efficiency.

• Ensure the integrity, reliability, and security of data through robust testing and validation

practices.

• Support the implementation of data governance practices, working closely with the Data QA

Specialist and Data Governance Lead.

• Monitor and troubleshoot data pipeline performance issues, proactively resolving bottlenecks and

incidents.

• Contribute to the design and implementation of data models and schemas that meet business

requirements.

• Stay updated on emerging technologies and best practices, recommending improvements to

existing processes and tools.

THE STUFF THAT SETS YOU APART

Must -Have Experience:

• 4 + years of experience in data engineering or a similar role.

• Hands -on experience building and maintaining data pipelines, ETL processes, and integrations.

• Proficiency in programming languages commonly used in data engineering (e.g., Python, SQL,

Scala).

• Experience with cloud data platforms such as Snowflake or Azure.

• Solid understanding of data modelling principles and database management systems.

Technical Skills:

• Knowledge of big data frameworks and processing tools (e.g., Snowflake, Airflow, dbt, Apache

Spark, Hadoop).

• Familiarity with DevOps practices, including CI/CD pipelines and version control systems (e.g., Git).

• Understanding of data governance principles, quality frameworks, and security best practices.

• Experience with containerization and orchestration tools (e.g., Docker, Kubernetes) is a plus.