Data Engineer

Responsibilities:

• Data Engineering and Modelling: Develop and maintain analytics-ready datasets, transformations, and date models within Databricks and Azure-based data platforms to support reporting and business intelligence initiatives.
• Databricks Development: Build and support data transformation workflows, notebooks, and analytics processes utilising Databricks within the Azure cloud environment.
• Analytics and Reporting: Support development and optimisation of Power BI and Tableau dashboards, datasets, and reporting solutions that deliver actionable business insights.
• Cloud Data Platform Support: Collaborate with senior engineers to support Azure-based analytics architecture, data pipelines, integrations, and reporting environments.
• Data Transformation and ETL/ELT: Support pipelines and transformation logic to prepare high-quality, analytics-ready datasets.
• Stakeholder Collaboration: Work closely with business stakeholders, data engineers, and BI developers to understand requirements and deliver tailored analytics solutions.
• Data Governance and Optimisation: Implement and uphold best practices for data documentation, access control, and performance tuning.
• User Enablement: Provide training, support, and best practice guidance to promote adoption of self-service analytics tools across the organisation.
• Performs other duties as assigned.

Requirements:

• To perform this job successfully, an individual must be able to perform each essential duty satisfactorily. The requirements listed below are representative of the knowledge, skill, and/or ability required. Reasonable accommodation may be made to enable individuals with disabilities to perform the essential functions.
• Bachelor's degree in data analytics, computer science, information technology, engineering, or a related field (master's degree preferred).
• 2-4 years of experience in data analytics, analytics engineering, business intelligence, or data engineering-related roles.
• Proven ability to develop executive-level dashboards using Power BI and/or Tableau.
• Strong experience with SQL for data querying, modelling, and transformation.
• Experience working with Databricks, Azure cloud technologies, and modern analytics engineering workflows preferred.
• Experience supporting data transformation, ETL/ELT development, and analytics-ready dataset creation using SQL and cloud-based technologies.
• Familiarity with Azure cloud services such as Azure Data Factory, Data Lake, Synapse, and Databricks preferred.
• Familiarity with scripting languages (e. g., Python, R) for data manipulation is a plus.
• Excellent communication skills to translate technical concepts to non-technical stakeholders.
• Strong problem-solving and analytical skills.
• Ability to work independently and collaboratively in a fast-paced environment.

Compliance, Ethics and Professionalism:

• Highly ethical and moral standards.
• Adherence to Compliance Standards and Policies.
• Adherence to the Employee/HR Manual and company policies/procedures.
• Sensitivity with confidential information (both business and patient information).
• Positive and professional attitude.
• Strong ability to work collaboratively with others in a team atmosphere.

Skills

azure, databricks, sql