MLOps Architect (Databricks Specialist)

Overview

Remote
Depends on Experience
Contract - W2
Contract - 12 Month(s)

Skills

Data Architecture
Apache Kafka
TensorFlow
PySpark
Python
SQL

Job Details

Job Description:

* 12+ years in IT experience with a minimum 10+ Years of experience in data engineering, data platform, and analytics.

* Projects delivered with hands-on experience in development on Databricks.

* Working knowledge of any one cloud platform (AWS, Azure, or Google Cloud Platform).

* Deep experience with distributed computing with Spark, including knowledge of Spark runtime internals.

* Familiarity with CI/CD for production deployments.

* Working knowledge of MLOps.

* Current knowledge across the breadths of Databricks product and platform features.

* Familiarity with optimization for performance and scalability.

* Completed data engineering professional certification and required classes.

* Minimum qualifications:

* Educational Background: Bachelor s degree in Computer Science, Information Technology, or a related field (or equivalent experience).

Technical Skills:

* Expert-level proficiency in Spark Scala, Python, and PySpark.

* In-depth knowledge of data architecture, including Spark Streaming, Spark Core, Spark SQL, and data modeling.

* Hands-on experience with various data management technologies and tools, such as Kafka, StreamSets, and MapReduce.

* Proficient in using advanced analytics and machine learning frameworks, including Apache Spark MLlib, TensorFlow, and PyTorch, to drive data insights and solutions.

* Databricks Specific Skills:

* Extensive experience in data migration from on-premises to cloud environments and in implementing data solutions on Databricks across cloud platforms (AWS, Azure, Google Cloud Platform).

* Skilled in designing and executing end-to-end data engineering solutions using Databricks, focusing on large-scale data processing and integration.

* Proven hands-on experience with Databricks administration and operations, including notebooks, clusters, jobs, and data pipelines.

* Experience integrating Databricks with other data tools and platforms to enhance overall data management and analytics capabilities.

Certifications:

* Certification in Databricks Engineering (Professional)

* Microsoft Certified: Azure Data Engineer Associate

* Google Cloud Platform Certified: Professional Google Cloud Certified.

* AWS Certified Solutions Architect Professional

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