Data Architect
3 weeks ago
About the Role
We are seeking a Senior Data Engineer with expertise in designing and implementing scalable data solutions, including robust data pipelines. Strong proficiency in ETL processes, MLOps practices for efficient model deployment, and utilizing technologies such as Databricks, DataLake, Vector DB, and Feature Store are essential.
Key Responsibilities:
- Design, optimize, and maintain scalable data pipelines using PySpark (Apache Spark), Python, Databricks, and Delta Lake.
- Implement MLOps practices for efficient deployment and monitoring of machine learning models.
- Develop strategies and tools for detecting and mitigating data drift.
- Utilize Vector DB for effective data querying and management.
- Establish and manage a Feature Store to centralize and share feature data for machine learning models.
- Ensure data integrity and quality throughout all stages of the pipeline.
- Collaborate with teams and stakeholders to deliver impactful data solutions.
Requirements:
- 5-8 years of experience in designing and implementing effective data solutions.
- 5+ years of experience in Databricks, Delta Lake, PySpark (Apache Spark), MLOps, Data Drift Detection, Vector DB, and Feature Store.
Soft Skills:
- Collaborate effectively with cross-functional teams and stakeholders to deliver impactful data solutions.
- Demonstrate strong communication skills to articulate complex technical concepts to non-technical stakeholders.
- Exhibit problem-solving skills to address data-related challenges and optimize processes.
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