Capgemini
This role is offered by Capgemini. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more.
Base Pay $110,000.00/yr - $115,000.00/yr
Location Atlanta, GA / Chicago, IL (Hybrid)
Key Responsibilities
Design, build, and maintain scalable ETL/ELT pipelines using Azure Data Factory, Synapse Pipelines, and Databricks.
Ingest, transform, and curate structured and unstructured data from diverse sources for AI/ML consumption.
Optimize data workflows for performance, reliability, and cost-efficiency.
Enable data access and preparation for Azure AI services including Azure Machine Learning, Azure OpenAI, and Cognitive Services.
Collaborate with data scientists and ML engineers to operationalize AI models using MLOps and GenAI Ops practices.
Support RAG (Retrieval-Augmented Generation) and other GenAI patterns through data engineering best practices.
Implement CI/CD pipelines for data workflows using Azure DevOps or GitHub Actions.
Automate infrastructure provisioning using Terraform, Bicep, or ARM templates.
Monitor and troubleshoot data pipelines and cloud resources using Azure Monitor and Log Analytics.
Skills and Qualifications
8–10+ years of experience in data engineering, cloud platforms, and big data technologies.
Experience with Python, Spark, SQL, and distributed data processing.
Familiarity with AI/ML workflows and tools such as Azure ML, MLflow, and OpenAI APIs.
Understanding of data governance, security, and compliance in cloud environments.
Benefits
Healthcare including dental, vision, mental health and well‑being programs.
Financial well‑being programs such as 401(k) and Employee Share Ownership Plan.
Paid time off and paid holidays.
Paid parental leave.
Family‑building benefits like adoption assistance, surrogacy and cryopreservation.
Social well‑being benefits like subsidized backup child/elder care and tutoring.
Mentoring, coaching and learning programs.
Employee Resource Groups.
Disaster Relief.
Equal Employment Opportunity Capgemini is an Equal Opportunity Employer encouraging diversity in the workplace. All qualified applicants will receive consideration for employment without regard to race, national origin, gender identity/expression, age, religion, disability, sexual orientation, genetics, veteran status, marital status or any other characteristic protected by law.
Reasonable Accommodations Capgemini is committed to providing reasonable accommodations during our recruitment process. If you need assistance or accommodation, please reach out to your recruiting contact.
Salary Transparency Capgemini discloses salary range information in compliance with state and local pay transparency obligations. The disclosed range represents the lowest to highest salary we, in good faith, believe we would pay for this role at the time of this posting, although we may ultimately pay more or less than the disclosed range, and the range may be modified in the future.
Seniority, Employment Type, Job Function
Mid‑Senior level
Full‑time
Finance, Consulting, and Business Development
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Base Pay $110,000.00/yr - $115,000.00/yr
Location Atlanta, GA / Chicago, IL (Hybrid)
Key Responsibilities
Design, build, and maintain scalable ETL/ELT pipelines using Azure Data Factory, Synapse Pipelines, and Databricks.
Ingest, transform, and curate structured and unstructured data from diverse sources for AI/ML consumption.
Optimize data workflows for performance, reliability, and cost-efficiency.
Enable data access and preparation for Azure AI services including Azure Machine Learning, Azure OpenAI, and Cognitive Services.
Collaborate with data scientists and ML engineers to operationalize AI models using MLOps and GenAI Ops practices.
Support RAG (Retrieval-Augmented Generation) and other GenAI patterns through data engineering best practices.
Implement CI/CD pipelines for data workflows using Azure DevOps or GitHub Actions.
Automate infrastructure provisioning using Terraform, Bicep, or ARM templates.
Monitor and troubleshoot data pipelines and cloud resources using Azure Monitor and Log Analytics.
Skills and Qualifications
8–10+ years of experience in data engineering, cloud platforms, and big data technologies.
Experience with Python, Spark, SQL, and distributed data processing.
Familiarity with AI/ML workflows and tools such as Azure ML, MLflow, and OpenAI APIs.
Understanding of data governance, security, and compliance in cloud environments.
Benefits
Healthcare including dental, vision, mental health and well‑being programs.
Financial well‑being programs such as 401(k) and Employee Share Ownership Plan.
Paid time off and paid holidays.
Paid parental leave.
Family‑building benefits like adoption assistance, surrogacy and cryopreservation.
Social well‑being benefits like subsidized backup child/elder care and tutoring.
Mentoring, coaching and learning programs.
Employee Resource Groups.
Disaster Relief.
Equal Employment Opportunity Capgemini is an Equal Opportunity Employer encouraging diversity in the workplace. All qualified applicants will receive consideration for employment without regard to race, national origin, gender identity/expression, age, religion, disability, sexual orientation, genetics, veteran status, marital status or any other characteristic protected by law.
Reasonable Accommodations Capgemini is committed to providing reasonable accommodations during our recruitment process. If you need assistance or accommodation, please reach out to your recruiting contact.
Salary Transparency Capgemini discloses salary range information in compliance with state and local pay transparency obligations. The disclosed range represents the lowest to highest salary we, in good faith, believe we would pay for this role at the time of this posting, although we may ultimately pay more or less than the disclosed range, and the range may be modified in the future.
Seniority, Employment Type, Job Function
Mid‑Senior level
Full‑time
Finance, Consulting, and Business Development
#J-18808-Ljbffr