Senior Data Ops Engineer

Description

Title: Senior Data Ops Engineer

Location: Irving, TX

Alternative Location: Charlotte, NC, Chandler, AZ, Des Moines, IA, Minneapolis, MN

Duration: 12 months

Work Engagement: W2

Work Schedule: Hybrid 3 days in office/2 days remote

Benefits on offer for this contract position: Health Insurance, Life insurance, 401K and Voluntary Benefits

Summary:

In this contingent resource assignment, you may: Consult on complex initiatives with broad impact and large-scale planning for Specialty Software Engineering. Review and analyze complex multi-faceted, larger scale, or longer-term Specialty Software Engineering challenges that require in-depth evaluation of multiple factors, including intangibles or unprecedented factors. Contribute to the resolution of complex and multi-faceted situations requiring solid understanding of the function, policies, procedures, and compliance requirements that meet deliverables. Strategically collaborate and consult with client personnel. Required Qualifications: Specialty Software Engineering experience, or equivalent demonstrated through one or a combination of the following: work or consulting experience, training, military experience, education.

Key Responsibilities:

 Implement and operationalize modern AI-enabled data capabilities on Google Cloud to ingest, transform, and distribute data for a variety of big data apps
 Leverage AI/Agentic frameworks to automate data management, governance, and data consumption capabilities - data pipelines, data quality, metadata, data compliance, etc.
 Work within a matrix org. with principal engineers, product managers, and data engineers to roadmap, plan, and deliver key data capabilities based on priority

Key Requirements:

• Applicants must be authorized to work for ANY employer in the U.S. This position is not eligible for visa sponsorship.

Demonstrable skills (recent) using AI tools such as LangChain, LangGraph/ADK, agentic frameworks, RAG, GraphRAG, and using MCP to build agent-based data capabilities
 data engineering including hands-on experience working with Cloud data solutions: creating/supporting Spark based ingestion and processing
 Data lakehouse architecture and design, including hands-on experience with Python, pySpark, Kafka, Airflow, Google Cloud Storage, BigQuery, Data Proc, Cloud Composer
 Hands-on experience developing data flows using Kafka, Flink, and Spark streaming

Desired Qualifications:
 Proven experience using AI to auto-generate data engineering related code, context engineering and prompt engineering
 Deep background on cloud-based data lakes and warehouses, and automated data pipelines
 Public cloud certifications such as GCP Professional Data Engineer, Azure Data Engineer, or AWS Specialty Data Analytics
 Web based UI development using React and Node JS is a plus