Data Engineering LP working on data models & pipelines for Acuity's analytics initiatives. Collaborating with teams using modern tools in a hybrid work environment.
Responsibilities
Assist in architecting, implementing, and deploying data pipelines and models that support Acuity’s analytics and AI initiatives using tools like Azure Data Factory, Databricks, and SQL
Perform data exploration, transformation, and validation to ensure accuracy and usability for business reporting and decision-making
Work closely with engineers, product managers, and data scientists to understand data needs, translate business requirements into data solutions, and support integration of ML/AI models
Help monitor and maintain data quality standards, documentation, and lineage; learn and apply best practices for security, compliance, and governance (e.g., SOX, GDPR)
Contribute to building curated datasets and semantic layers that power dashboards, self-service analytics, and predictive insights
Support production data processes, troubleshoot issues, and assist in optimizing pipeline performance and cost efficiency
Requirements
Bachelors in Computer Science, Information Science, Mathematics, or related technical field required
Master’s degree preferred
Knowledge of SQL, data modeling and at least one programming language (e.g., Python, C++, C#, Scala)
Strong problem-solving, collaboration, and communication skills
Curious, self-driven, analytical and excited to play with data
Ability to thrive in a fast paced work environment
Microsoft Certified: Azure Data Engineer Associate certification preferred
Experience with real-time data processing (Event Hubs, Kafka, Delta Live Tables, Azure Stream Analytics) preferred
Exposure to MLOps or integrating ML models into data pipelines preferred
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