Responsibilities:

Work closely with Data Scientists, Business Team and Engineers to understand business requirements, translating those requirements into technical architectures, and ensuring the effective integration of Databricks with other enterprise systems.
Recommend best practices around data engineering, machine learning, and analytics workflows, as well as guiding teams in the adoption of efficient architecture patterns.
Define project scope, set technical direction, and troubleshoot complex problems.
Lead the development of proof-of-concept solutions, evaluate new platform features, and ensure that security and compliance standards are met.
Plan and execute Migration strategies to transition on prem data warehouse and Datalake into cloud based Databricks
Develop reusable frameworks for Data Engineering and Machine Learning Data Pipelines
Explore AI and Gen AI solutions for business requirements and provide solutions to adopt them.

Qualifications:

Proven expertise in implementing Lakehouse and Delta Lake using Databricks.
Strong PySpark and Python experience
Databricks (AWS) Platform Architect Certification
Familiarity with ML Ops/LLM Ops and distributed systems.
Experience with Big Data platform like Cloudera Hadoop and Could platforms like

AWS, GCP.

Solid understanding of system design patterns, scalability, observability, and performance tuning.
Strong analytical and problem-solving skills.
Passion for exploring and building with emerging technologies.

Good to

Have Skills:

AWS EKS Experience, Dockers and Containers Salary Range- $125,000-$140,000 a year #LI-CO1 #LI-SN1

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