Senior Data Engineer

This Senior Data Engineer will be the engine behind our platform's acceleration. Working alongside our infrastructure and automation lead, this role transforms our ability to build reliable, scalable data pipelines that power everything from executive dashboards to AI predictions. Without this foundation, the insights layer cannot exist.

Responsibilities:

• Build and optimise dbt models across staging, intermediate, domain, and marts layers following healthcare data best practices.
• Design and implement data pipelines for healthcare vendor data ingestion, transformation, and quality validation.
• Develop automated monitoring and alerting to catch data issues before they impact downstream analytics.
• Create ML feature engineering pipelines that prepare data for predictive models in SageMaker and Bedrock.
• Optimise Redshift performance through query tuning, table design, and workload management.
• Build CI/CD pipelines for reliable, automated deployments across environments.
• Document data models and pipelines to enable team knowledge sharing and platform maintainability.

Requirements:

• Bachelor's degree in a relevant field.
• 4-7 years of relevant work experience, including 3+ years of data engineering experience with SQL and Python.
• Hands-on experience with DBT or similar transformation frameworks.
• Experience with cloud data warehouses (Redshift, Snowflake, or BigQuery).
• Strong understanding of data modelling, ETL/ELT patterns, and data quality.
• Ability to work independently and collaborate across distributed teams.

Behavioural Competencies:

• Ability to produce high-quality results, work in a collaborative environment by embracing diverse perspectives and with a solution-based approach.
• Ability to adapt communication clearly and concisely based on team dynamics and express thoughts and ideas effectively.
• Ability to engage effectively with peers and stakeholders to build trust and reliable working relationships.
• Ability to understand business processes, implement innovative solutions, and guide juniors on continuous improvement by constantly updating oneself on current technology and trends.
• Inquisitive to understand customer and business expectations while creating value addition on technical solutions.

Good to Have:

• Healthcare data experience (claims, eligibility, pharmacy, clinical).
• AWS experience (Redshift, SageMaker, Lambda, Step Functions).
• ML feature engineering or model deployment experience.
• CI/CD tools (GitHub Actions, Jenkins, or similar).
• Workflow orchestration tools (Airflow, Dagster, or similar).