Lead Data Engineer

Overview

We are seeking a highly capable Data Engineer with hands-on experience to build, test and optimize scalable data pipelines and analytics solutions. Maintain awareness of emerging approaches in data architecture, data modelling, pipeline design, automation and DevOps practices relevant to the analytics ad data platform landscape.

This role will partner closely with data architect, data scientists, analysts, product teams, and business stakeholders to deliver production-grade data products that drive operational and strategic decision-making.

Key Responsibilities

As a Data Engineer, you will

• Design, build, and maintain robust ETL/ELT pipelines for healthcare datasets

• Contribute to the design and automation of data flows that replace manual processes and improve efficiency

• Develop reusable data engineering frameworks and CI/CD pipelines

• Contribute to data quality and metadata requirements

• Collaborate with Data, BI and Architecture colleagues

• Ensure data engineering solutions comply with information governance, security and data protection requirements

• Create clear technical documentation for pipelines, models and processes

• Good understanding of DevOps principles including version control and controlled release

• Ability to communicate complex technical concepts clearly to technical and non-technical audiences

Required Qualifications

• Bachelor's or Master's degree in computer science, Engineering, Information Systems, or related field

• 3+ years (Mid-level) or 5+ years (Senior) of data engineering experience

• Strong proficiency in:

• Python

• SQL

• Spark (PySpark or SparkSQL)

• Power BI

• Experience building production data pipelines in cloud environments (AWS, Azure, or GCP)

• Understanding of data modelling, schema design, and metadata management

• Familiarity with CI/CD and version-controlled development practices

• Understanding of data warehousing and ELT/ETL patterns

Desirable

• Strong understanding of data governance, security, and access control in enterprise reporting

• Bachelor's or Master's degree in computer science, Engineering, Information Systems, or related field

• 3+ years (Mid-level) or 5+ years (Senior) of data engineering experience

• Strong proficiency in:

• Python

• SQL

• Spark (PySpark or SparkSQL)

• Power BI

• Experience building production data pipelines in cloud environments (AWS, Azure, or GCP)

• Understanding of data modelling, schema design, and metadata management

• Familiarity with CI/CD and version-controlled development practices

• Understanding of data warehousing and ELT/ETL patterns

Desirable

• Strong understanding of data governance, security, and access control in enterprise reporting