Multi-platform familiarity
Deep experience with **Databricks**, **Snowflake**, or other major cloud data warehousing/lakehouse solutions
Proficiency with cloud-native AI/ML platforms (e.g., AWS Bedrock / Sagemaker, Azure ML, Google AI Platform/Vertex AI)
Strong experience with major cloud providers (AWS, Azure, GCP)
Specialized knowledge of the data ecosystem, including data ingestion, ETL/ELT processes, data warehousing, data lakes, and real-time analytics
Awareness of current trends in machine learning (supervised, unsupervised, deep learning), MLOps, and advanced AI concepts
Deep understanding of **MLOps** principles and tools for continuous integration/continuous delivery (CI/CD) of machine learning models
Familiarity with containerization (Docker) and orchestration (Kubernetes)
Experience with **software estimation**, work planning, and building project plans within time/cost constraints
Ability to clearly break down complex data and AI concepts to both technical and non-technical individuals
Experience delivering software or data solutions in an agency/client-service environment
Excellent verbal and written communication skills

Benefits

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

DatabricksSnowflakeAWS BedrockSagemakerAzure MLGoogle AI PlatformVertex AIMLOpsDockerKubernetes

Soft Skills

communicationtechnical architecturework planningproject planningcomplex problem breakdownclient-service delivery