- Company Name
- McGregor Boyall
- Job Title
- Analytics Engineer
- Job Description
-
**Job Title:** Analytics Engineer
**Role Summary:**
Design, build, and maintain scalable data infrastructure on the modern data stack (Azure Databricks, Azure Data Factory, dbt, SQL, Python, Power BI). Serve as the liaison between data engineering and analytics, delivering reliable data pipelines, dimensional models, and self‑service analytics to enable data‑driven decision making.
**Expectations:**
- Minimum 5 years of experience in data or analytics engineering.
- Proficient in SQL, Python, and dbt.
- Hands‑on experience with Azure (or comparable cloud) data services.
- Strong grasp of data architecture, modeling, and governance.
- Familiarity with CI/CD, Git, and infrastructure‑as‑code practices.
- Ability to mentor junior staff and uphold coding standards.
- Excellent problem‑solving and communication skills.
**Key Responsibilities:**
- Develop, schedule, and maintain data pipelines using Azure Databricks and Azure Data Factory.
- Create and manage dimensional models and transformation workflows with dbt.
- Implement automated data quality checks, monitoring, and alerting.
- Build and support self‑service Power BI dashboards for business users.
- Document technical designs, processes, and coding standards.
- Collaborate with engineers, analysts, and business stakeholders to gather requirements and deliver solutions.
- Mentor junior team members and promote best practices across the data team.
**Required Skills:**
- SQL (advanced)
- Python (data engineering libraries)
- dbt (modeling, testing, documentation)
- Azure Databricks & Azure Data Factory (pipeline orchestration)
- Power BI (reporting & dashboarding)
- Data modeling (star/snowflake, dimensional design)
- Data governance & quality frameworks
- CI/CD pipelines, Git version control, IaC concepts (e.g., Terraform, ARM)
- Strong analytical, troubleshooting, and communication abilities
**Required Education & Certifications:**
- Bachelor’s degree in Computer Science, Information Systems, Data Science, Engineering, or a related quantitative field (or equivalent professional experience).
- Relevant certifications (e.g., Azure Data Engineer Associate) are a plus but not mandatory.