Architecting, developing, and optimizing scalable data pipelines, integrations, and warehouse solutions that support analytics, artificial intelligence (AI), and machine learning initiatives across the organization.
Requirements
- Advanced proficiency in SQL and experience with relational and dimensional data modeling.
- Hands-on experience with modern data platforms such as Microsoft Fabric, Azure Synapse, or Databricks.
- Strong understanding of ETL/ELT concepts, data pipelines, and data warehouse best practices.
- Familiarity with AI/ML data preparation techniques, such as feature engineering, data normalization, and model input pipeline design.
- Experience with cloud data ecosystems (Azure, AWS, or GCP).
- Exposure to ML Ops or integrating data pipelines with machine learning platforms.
- Familiarity with infrastructure automation and DevOps (CI/CD pipelines, Git, etc.).
Responsibilities
- Design, build, and maintain robust ETL/ELT pipelines and data workflows using tools such as Microsoft Fabric, Azure Data Factory, or Databricks.
- Develop and optimize SQL-based transformations, ensuring high performance and data reliability across large, complex datasets.
- Engineer and maintain the data warehouse and lakehouse architecture, enabling efficient storage, retrieval, and processing of both structured and unstructured data.
- Prepare and curate high-quality, feature-ready datasets to support AI and machine learning models, ensuring data consistency, accuracy, and scalability.
- Implement and monitor data quality, validation, and governance frameworks to ensure data integrity and compliance.
- Automate data ingestion from multiple systems (ERP, CRM, operational databases, APIs) to create unified, analytics-ready datasets.
- Collaborate with data scientists, analysts, and business stakeholders to ensure that data pipelines and data models align with analytical and AI use cases.
Other
- 5+ years of experience in data engineering, ETL development, or data warehousing.
- Strong communication skills to effectively collaborate across technical and non-technical teams.
- Candidates that accept an offer of employment are required to undergo and successfully complete a pre-employment physical examination.
