Store AI Agent - Onshore Data Engineer (Python, Pytorch, NodeJS)

Capgemini; Dallas (TX); On-site; USD 54,000 - 85,000; Full time

Benefits offered by this job

Medical benefits

Retirement benefits

Career growth opportunities

Job summary

Capgemini is hiring a Store AI Agent - Onshore Data Engineer to design, build, and optimize scalable data and ML pipelines. You will leverage Databricks, PySpark, Python, and PyTorch to enable AI/ML initiatives, feature stores, and robust data platforms across cloud environments.

The role emphasizes data modeling, Delta Lake governance, and collaborative work with data scientists to operationalize models and ML workflows with strong DevOps practices.

Qualifications

• 5+ years of data engineering experience in scalable environments.
• 3+ years with Databricks and cloud-based data platforms.
• Experience supporting ML/AI use cases using PyTorch.
• Strong knowledge of data lakes, warehousing, and ETL/ELT patterns.

Responsibilities

• Design, develop, and maintain scalable data pipelines using Databricks and Python.
• Build batch and real-time data ingestion from diverse sources.
• Develop ETL/ELT solutions for analytics and AI/ML workloads.
• Implement data quality checks, monitoring, and observability.
• Optimize Databricks jobs, notebooks, and workflows for cost/performance.
• Design Delta Lake architectures and metadata management.
• Collaborate with data scientists to prepare datasets and feature stores.
• Support model training and inference infrastructure on Databricks.
• Integrate ML workflows with MLOps pipelines and CI/CD processes.
• Apply DataOps and MLOps best practices.

Skills

Python

PyTorch

PySpark

Spark

SQL

Data Modeling

REST APIs

Git

CI/CD

NLP

Education

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

Tools

Databricks Platform

Databricks Workflows

Delta Lake

Unity Catalog

AWS

Azure Data Factory

Docker

Kubernetes

Git

CI/CD

REST APIs

Job description

Store AI Agent - Onshore Data Engineer (Python, Pytorch, NodeJS) (Contract)

Contract (9 months 5 days)

Published 3 days ago

Databricks Platform

data modeling

mlops

DevOps & CI/CD

PySpark/Python

We are seeking a highly skilled Data Engineer with strong expertise in Databricks, Python, and PyTorch to design, develop, and optimize scalable data and machine learning pipelines. The ideal candidate will be responsible for building cloud‑native data platforms, enabling advanced analytics, and supporting AI/ML initiatives through robust data engineering practices.

This role requires hands‑on experience in large‑scale data processing, feature engineering, model deployment support, and performance optimization across modern data ecosystems.

Key Responsibilities:

Design, develop, and maintain scalable data pipelines using Databricks, PySpark, and Python.

Build and optimize batch and real‑time data ingestion frameworks from diverse data sources.

Develop ETL/ELT solutions to support enterprise data warehousing, analytics, and AI/ML workloads.

Implement data quality checks, validation frameworks, monitoring, and observability solutions.

Optimize Databricks jobs, notebooks, clusters, and workflows for performance and cost efficiency.

Design and maintain Delta Lake architectures, data models, and metadata management solutions.

Collaborate with Data Scientists and ML Engineers to prepare training datasets and feature stores.

Support development and deployment of deep learning solutions using PyTorch.

Develop scalable feature engineering pipelines and data transformation frameworks.

Enable model training, experimentation, and inference infrastructure on Databricks.

Integrate ML workflows with MLOps pipelines and CI/CD processes.

Implement DataOps and MLOps best practices.

Work with cloud‑native services for storage, security, monitoring, and orchestration.

Support infrastructure‑as‑code and environment automation initiatives.

Partner with business, analytics, and data science teams to understand requirements and translate them into technical solutions.

Ensure compliance with data governance, privacy, and security standards.

Participate in architecture reviews and technology evaluations.

Required Skills:

Technical Skills:

Strong experience with Databricks Platform

Expertise in Python

Strong hands‑on experience with PySpark

Experience with PyTorch for machine learning and deep learning workloads

Knowledge of Delta Lake, Unity Catalog, and Databricks Workflows

Experience with ETL/ELT pipeline development

Strong SQL and data modeling skills

Experience with distributed computing and big data architectures

Knowledge of REST APIs and data integration patterns

Git version control and CI/CD tools

Experience with one or more:

AWS

Data Technologies:

Spark

Kafka/Event Streaming

Azure Data Factory or equivalent integration tools

Data Lake architectures

Data Warehousing solutions

Preferred Skills:

Experience with GenAI and LLM data pipelines.

Knowledge of MLflow and MLOps frameworks.

Hands‑on experience with Docker and Kubernetes.

Experience with real‑time streaming architectures.

Familiarity with vector databases and AI platforms.

Certifications in Databricks or Cloud platforms.

Qualifications:

Bachelor's or Master's degree in Computer Science, Data Engineering, Information Systems, or related field.

5+ years of experience in Data Engineering.

3+ years of experience with Databricks and cloud‑based data platforms.

Experience supporting machine learning and AI use cases using PyTorch.

Nice-to-Have Experience:

Retail, QSR, Restaurant Technology, Digital Commerce, or Customer Analytics domains.

AI/ML and advanced analytics implementations.

The pay range that the employer in good faith reasonably expects to pay for this position is $39.30/hour - $61.40/hour. Our benefits include medical, dental, vision and retirement benefits. Applications will be accepted on an ongoing basis.

Tundra Technical Solutions is among North America’s leading providers of Staffing and Consulting Services. Our success and our clients’ success are built on a foundation of service excellence. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. Qualified applicants with arrest or conviction records will be considered for employment in accordance with applicable law, including the Los Angeles County Fair Chance Ordinance for Employers and the California Fair Chance Act. Unincorporated LA County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: client provided property, including hardware (both of which may include data) entrusted to you from theft, loss or damage; return all portable client computer hardware in your possession (including the data contained therein) upon completion of the assignment, and; maintain the confidentiality of client proprietary, confidential, or non-public information. In addition, job duties require access to secure and protected client information technology systems and related data security obligations.