Senior AI/ML Data Platform Engineer

Creative Global Consulting; Linthicum (MD); On-site; USD 130,000 - 200,000; Part time

Job summary

Creative Global Consulting seeks a Senior AI/ML Data Platform Engineer to lead architecture and development of enterprise data products and AI-enabled services. The role emphasizes scalable platforms, real-time streaming, data quality, governance, API design, and AI integration into data workflows.

Must have 10+ years in data/ML engineering, strong SQL and Python, and experience with major cloud data services. On-site in Linthicum Heights, MD. 12+ months contract.

Qualifications

• 10+ years in data engineering, ML engineering, or data platform development with 2+ years on production data products.
• Bachelor's degree in CS/DS/Engineering; master's preferred.
• Expert SQL and strong Python programming skills.
• Experience with major cloud data platforms and data services.
• Production experience with streaming and real-time data technologies.
• Strong data modeling, governance, and API design capabilities.

Responsibilities

• Lead architecture and development of shared enterprise data products and AI-enabled services.
• Focus on scalable data platforms, real-time streaming, data quality, and governance.
• Design APIs and integrate AI/ML capabilities into data workflows.

Skills

Data engineering

ML engineering

Data platform development

SQL

Python

Amazon Redshift

AWS Glue

Azure Synapse

Azure Data Factory

BigQuery

Dataflow

Databricks

Snowflake

Kafka

Kinesis

Flink

Spark Structured Streaming

Data modeling

Data vault

Lakehouse

Data mesh

Data quality

Data catalogs

Data lineage

API design

Data contracts

Event-driven architectures

ML integration

Data governance

Leadership

Technical docs

Mentoring

Cross-team collaboration

Education

Bachelor's degree in Computer Science, Data Science, Engineering, or related field

Master's degree preferred

Tools

Amazon Redshift

AWS Glue

Azure Synapse

Azure Data Factory

BigQuery

Dataflow

Databricks

Snowflake

Job description

Location

Linthicum Heights, MD (On-site)

Duration

12+ Months Contract

Summary

The Senior AI/ML Data Platform Engineer will lead the architecture, development, and continuous improvement of shared enterprise data products and AI-enabled data services. The role focuses on scalable data platforms, real-time streaming, data quality, governance, API design, and integration of AI/ML capabilities into data workflows.

Required Skills

• 10+ years of experience in data engineering, ML engineering, or data platform development, including 2+ years designing or operating production data products or data services.
• Bachelor's degree in Computer Science, Data Science, Engineering, or a related field; master's degree preferred.
• Expert-level SQL and strong Python programming skills.
• Experience with AWS, Azure, or GCP data platforms, including Amazon Redshift, AWS Glue, Azure Synapse, Azure Data Factory, BigQuery, Dataflow, Databricks, or Snowflake.
• Production experience with Apache Kafka, Amazon Kinesis, Apache Flink, or Spark Structured Streaming.
• Strong understanding of data modeling and architecture patterns, including data vault, lakehouse, and data mesh.
• Experience with data quality frameworks, data catalogs, data lineage, API design, data contracts, and event-driven architectures.
• Experience integrating ML models into data pipelines or developing AI-powered data services.
• Experience with data access controls, attribute-level masking, audit logging, and governance.
• Strong architectural leadership, technical documentation, mentoring, and cross-team collaboration skills.

Preferred Skills

• Data mesh, federated data architecture, and enterprise data product initiatives.
• LLM applications for text-to-SQL, document extraction, semantic search, and automated enrichment.
• Government, public sector, or highly regulated environments.
• Data privacy and security requirements, including PII protection, CJIS, HIPAA, and IRS Publication 1075, where applicable.
• NIST AI Risk Management Framework and responsible AI practices.
• Data platform FinOps, cloud cost attribution, storage tiering, and query optimization.