MLOPS Senior Lead Engineer
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Job Description
Structured overview of role & requirementsAbout This Role
Develop and maintain robust data pipelines for ML model development using Python, SQL, PySpark, and cloud platforms.
Lead design and implementation using Databricks platform including Delta Lake and workflow management.
Build and maintain shared tools and libraries (e.g., data engineering utilities, data quality libraries) used across teams to standardize processes.
Minimum Requirements
Bachelor’s or master’s degree in Computer Science, Data Science, Engineering, or related field.
8+ years professional experience including 4+ years with Python, SQL, PySpark, and bash scripting.
3+ years experience with Cloud Data Warehousing platforms (Redshift, Snowflake, Databricks SQL) and distributed frameworks like Spark.
2+ years hands-on experience with Databricks platform, and working knowledge of CI/CD tools, version control, and orchestration tools.
Ideal Candidate Profile
Strong expertise in software development lifecycle, engineering best practices, and API development especially in Python frameworks (Flask / FastAPI).
Experienced in containerization (Docker/Kubernetes) and building shared reusable libraries across multiple teams.
Proven ability to collaborate effectively with cross-functional technology and business teams to deliver scalable MLOps solutions.