AI/Data Engineer

Job summary

In this role, you will design, build, and operate modern data platforms and data products that facilitate analytics and AI-driven use cases. You will work closely with clients and cross-functional teams to deliver scalable, reliable, and compliant data solutions in complex enterprise environments.

Qualifications

• Over 6 years of experience as an AI/Data Engineer in enterprise settings, focusing on scalable data solutions for analytics and AI.
• Proven expertise in building and managing batch and near real-time data pipelines, ensuring reliability and performance.
• Familiarity with modern data platforms and lakehouse architecture, including tools like Databricks and Snowflake, and experience with cloud platforms such as Azure, AWS, or Google Cloud Platform.
• Proficient in Python and SQL, with a strong understanding of data engineering best practices, including incremental processing and data quality validation.
• Experience with data modeling techniques (e.g., Kimball, Data Vault) and distributed data formats (e.g., Parquet, Iceberg).

Responsibilities

• Design, build, and maintain scalable data pipelines and products that support analytics and AI use cases.
• Collaborate with data product owners and AI/ML specialists to support feature engineering and operationalize AI solutions.
• Implement data transformations using Python and SQL, ensuring pipelines are observable and resilient.
• Contribute to enterprise standards for data governance and compliance while optimizing pipeline performance.

Skills

• Strong collaboration and communication skills in enterprise settings.

Education

• Relevant degree in a related field is preferred.

Tools

• Experience with Databricks, Snowflake, and cloud platforms (Azure, AWS, Google Cloud Platform).