Acuity Inc. is seeking a Data Engineer to design, build, and optimize data pipelines on the Azure Data Platform, enabling analytics, BI, and AI/ML use cases across the enterprise.
Requirements
- Proficiency with Python, Databricks (PySpark/SQL), Azure Data Factory, and Data Lakehouse architectures.
- Strong SQL and data modeling skills, with experience in ETL/ELT development.
- Familiarity with Power BI datasets and semantic modeling concepts.
- Understanding of data governance, compliance (SOX, GDPR), and security best practices.
- Microsoft Certified: Azure Data Engineer Associate certification.
- Experience with real-time data processing (Event Hubs, Kafka, Delta Live Tables, Azure Stream Analytics).
- Exposure to MLOps or integrating ML models into data pipelines.
Responsibilities
- Design, develop, and maintain scalable ETL/ELT pipelines using Azure Data Factory, Databricks (PySpark/SQL).
- Ingest and transform data from structured and unstructured sources, supporting both batch and streaming use cases.
- Implement data quality, validation, and monitoring within pipelines to ensure reliability.
- Collaborate with ML/AI teams to prepare AI-ready datasets and support integration of ML models into production workflows.
- Build domain-oriented, enriched data layers that power BI dashboards, advanced analytics, and predictive models.
- Partner with BI Engineers to deliver optimized data models for Power BI semantic layers.
- Follow established data governance and security standards to handle PII/SPII and regulated data.
Other
- 3+ years of hands-on experience in data engineering roles.
- Strong problem-solving, collaboration, and communication skills.
- Work with business analysts and power users to promote adoption of consistent, governed data sources.
- Contribute to a culture of data literacy, ensuring stakeholders can confidently use data for decision-making.
- Collaborate cross-functionally with BI engineers, business analysts, and the ML/AI team to deliver end-to-end solutions.
