Atlanta, GA

Data Jobs in Atlanta, GA

60 jobs found

Include remote jobs

Today

Lead Data Engineer - Snowflake

Capgemini Atlanta, GA

Atlanta, GA

Today

$165k - $190k/yr Full time Manager Artificial Intelligence Cloud

Apply Now

Job Description

Capgemini is seeking a Lead Data Engineer to spearhead enterprise-scale Data and AI platform engineering on Snowflake. This onsite role in Atlanta, GA focuses on designing, building, and optimizing unified platform capabilities, governed data environments, and Snowflake-powered AI and ML enablement.

Responsibilities

Design and implement enterprise-wide Unified Data & AI Platforms leveraging Snowflake.
Architect and develop scalable Medallion Layer data models and frameworks across Bronze, Silver, and Gold.
Build and maintain high-performance ELT pipelines using Snowflake Dynamic Tables, dbt, Tasks & Stored Procedures, Snowpipe, and Snowflake Openflow Connect.
Develop AI-powered solutions using the Snowflake Cortex ecosystem, including Cortex Analyst, Cortex Search, Cortex Agents, Snowpark ML, Python, Streamlit, and MLOps frameworks.
Design and implement secure, governed data environments using Snowflake Horizon.
Establish and maintain Role-Based Access Control (RBAC) and Attribute-Based Access Control (ABAC) frameworks.
Collaborate with business and technology teams to develop customer-centric, domain-oriented data products.
Implement CI/CD processes and Git-integrated development workflows.
Monitor, optimize, and improve platform performance, scalability, and cost efficiency.
Partner with architects, data scientists, analysts, and business stakeholders to deliver data-driven solutions.
Ensure adherence to security, governance, compliance, and data quality standards.

Requirements

Bachelor's degree in Computer Science, Engineering, Information Systems, or a related field.
7+ years of experience in Data Engineering, Data Architecture, or Analytics Engineering.
Strong hands-on experience designing and implementing data platforms on Snowflake.
Proven expertise in Unified Data & AI platform architecture.
Proven expertise in Medallion architecture implementation.
Proven expertise in ELT/ETL pipeline development.
Proven expertise in data warehousing and data lake concepts.
Deep experience with Snowflake Dynamic Tables, dbt, Snowpipe, Tasks, and Stored Procedures.
Deep experience with Openflow Connect.
Hands-on experience with Snowflake AI and ML capabilities: Cortex Analyst, Cortex Search, Cortex Agents, Snowpark ML, Streamlit, Python, and MLOps practices.
Strong understanding of Snowflake security and governance capabilities, including Horizon.
Experience implementing RBAC and ABAC security models.
Experience with Git-based source control and modern ELT frameworks.
Strong cloud platform experience with AWS.
Excellent communication, stakeholder management, and problem-solving skills.

Key Technologies

Snowflake
Snowflake Dynamic Tables
dbt
Tasks, Stored Procedures, Snowpipe
Snowflake Openflow Connect
Snowflake Cortex ecosystem (Cortex Analyst, Cortex Search, Cortex Agents)
Snowpark ML, Python, Streamlit
MLOps frameworks
Snowflake Horizon
RBAC, ABAC
CI/CD, Git
AWS

Compensation and Location

Location: Atlanta, GA (onsite). Salary: USD 165,000 - 190,000 per year.

Benefits

Paid time off based on employee grade (A-F): Vacation 12-25 days depending on grade, plus company paid holidays, personal days, and sick leave.
Medical, dental, and vision coverage (or provincial healthcare coordination in Canada).
Retirement savings plans (for example, 401(k) in the U.S. or RRSP in Canada).
Life and disability insurance.
Employee assistance programs.
Other benefits as provided by local policy and eligibility.

View full job page →

Today

Snowflake Platform Admin + Data Engineer

Capgemini Atlanta, GA

Atlanta, GA

Today

$103k - $129k/yr Full time Automation Aws Data Lake Cloud

Apply Now

Job Description

Capgemini is seeking a platform-focused Snowflake administrator and data engineer to support enterprise Snowflake environments across development, testing, and production. This hybrid role in Atlanta, GA combines Snowflake operations with hands-on data engineering, governance, and automation so the platform can run securely, efficiently, and reliably.

You will be responsible for administering Snowflake at scale while building and optimizing ETL/ELT pipelines, implementing security controls, and improving performance and cost through continuous monitoring and tuning.

Key Responsibilities

Administer and support enterprise Snowflake environments across development, testing, and production
Manage Snowflake account setup including user provisioning, roles, permissions, and RBAC
Implement and maintain security controls such as SSO, MFA, dynamic data masking, row-level security, and secure data sharing
Configure and monitor resource monitors, virtual warehouses, and workload management to optimize performance and cost
Design and manage cross-region replication, disaster recovery, and business continuity solutions
Monitor platform health, troubleshoot operational issues, and share proactive recommendations for improvement
Design, develop, and maintain scalable ETL/ELT pipelines using AWS Glue and Snowflake
Build and optimize data ingestion frameworks from multiple cloud and on-premises data sources
Develop data models, transformations, and data warehouse solutions for analytics and reporting
Use Snowflake features including Snowpipe, Streams, Tasks, Stored Procedures, Time Travel, and Zero-Copy Cloning
Implement data quality, validation, and monitoring processes
Analyze query performance and optimize Snowflake workloads; tune SQL queries and storage utilization for efficiency
Establish platform standards, governance policies, and best practices
Develop CI/CD pipelines for Snowflake deployments and data engineering solutions
Automate administrative and operational activities using Python, SnowSQL, and scripting frameworks
Support Infrastructure as Code initiatives using Terraform or similar technologies

Required Qualifications

8+ years of IT experience, including 4+ years of hands-on Snowflake experience
Strong expertise in Snowflake administration and platform management
Hands-on experience with AWS Glue and cloud-based data engineering solutions
Advanced proficiency in SQL and Python

Technologies & Skills

Snowflake, AWS Glue, AWS S3, AWS IAM, AWS CloudWatch, AWS Lambda, AWS Secrets Manager
SQL, Python, SnowSQL, RBAC
SSO, MFA, dynamic data masking, row-level security
Snowpipe, Streams, Tasks, Stored Procedures, Time Travel, Zero-Copy Cloning
Snowpark, Data Sharing, Native Applications, Terraform (Infrastructure as Code)
CI/CD, including GitHub Actions, GitLab CI/CD, and Azure DevOps
Apache Airflow, SnowPro Core Certification, SnowPro Advanced Architect, SnowPro Advanced Data Engineer

Experience Managing

RBAC and security frameworks; Snowflake account administration
Data replication and disaster recovery
Data masking and governance controls
Understanding of Snowflake architecture, virtual warehouses, storage, compute, and optimization techniques
AWS services such as S3, IAM, CloudWatch, Lambda, and Secrets Manager
Troubleshooting, problem-solving, and analytical skills

Preferred Skills

Experience with Apache Airflow for orchestration
Knowledge of Snowpark, Snowpipe, Data Sharing, and Native Applications
Experience with Terraform and Infrastructure as Code
Experience with CI/CD tools such as GitHub Actions, GitLab CI/CD, or Azure DevOps
Snowflake certifications including SnowPro Core Certification, SnowPro Advanced Architect, and SnowPro Advanced Data Engineer
Experience with data governance, compliance, and enterprise security frameworks

Key Attributes

Strong platform ownership and an operational mindset
Ability to lead Snowflake architecture and administration best practices
Excellent stakeholder management and communication skills
Proven ability to work across engineering, analytics, and business teams
Proactive approach to performance tuning, automation, and cost optimization
Ability to mentor junior engineers and drive technical excellence

Benefits

Flexible work
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 including adoption assistance, surrogacy, and cryopreservation
Social well-being benefits such as subsidized back-up child/elder care and tutoring
Mentoring, coaching and learning programs; Employee Resource Groups
Disaster Relief
Paid time off based on employee grade (A-F) with policy-defined vacation ranges and additional personal and sick leave
Medical, dental, and vision coverage (or provincial healthcare coordination in Canada); retirement savings plans (401(k) in the U.S., RRSP in Canada)
Life and disability insurance; employee assistance programs
Other benefits as provided by local policy and eligibility

Location: Atlanta, GA (hybrid)
Salary: USD 103,330 - 128,656 per year
Experience: 4+ years minimum

View full job page →

Today

Sr Data Scientist - AI Engineer

Home Depot / THD Atlanta, GA

Atlanta, GA

Today

Full time Ai Ml Artificial Intelligence Automation

Apply Now

Job Description

Home Depot’s THD data science team is looking for a Senior Data Scientist to build production-ready AI capabilities that connect enterprise data to real workflows. This role focuses on establishing MLOps/LLMOps/AIOps operational frameworks and developing agentic AI solutions that can reason over data and orchestrate models into end-to-end execution.

What you will do

You will take ownership of solution development across advanced analytics, from designing models for large datasets to selecting and applying analytical methodologies that support business outcomes. A major part of the work includes ensuring outputs are executed with strong efficiency and quality, then translating results into clear recommendations for technical and non-technical leaders.

Design and develop algorithms and models that generate business insights from large datasets
Apply advanced analytical methodologies, including appropriate selection, utilization, and interpretation
Communicate insights and recommendation impacts to drive alignment and implementation
Prepare reports, updates, and presentations on progress for projects and solutions

You will also collaborate across teams to shape project direction and execution. This includes helping set goals, guiding prioritization, and supporting team quality through direction and coaching of more junior roles. The role includes coordination with managers and teams on workload and resource distribution, and involvement in recruiting and hiring efforts for the group.

Work with project teams and business partners to determine project goals
Provide direction on prioritization and ensure quality of work
Mentor and coach more junior roles to strengthen technical competencies
Collaborate with managers and teams on distribution of workload and resources
Support recruiting and hiring efforts for the team

Additional responsibilities include leveraging business context to improve solution approaches and building trusted relationships with internal customers and cross-functional teams. You will also support partner enablement by providing general education on advanced analytics, aligned with your understanding of IT needs required to solve business problems and create data science advantage.

Leverage business knowledge to shape the solution approach
Develop trust and collaboration with internal customers and cross-functional teams
Educate technical and non-technical partners on advanced analytics
Apply a deep understanding of IT needs to help the team tackle business problems
Actively pursue new business opportunities where data science can drive competitive advantage

On the technical side, you will continue exploring emerging capabilities and improving how solutions are delivered. This includes developing replicable, well-documented solutions (such as codified data products, project documentation, and process flowcharts), defining best practices for data analysis and model productionalization, and contributing to a reusable library of algorithms with clear documentation.

Stay current on key data science developments, technical skill sets, and additional data sources
Improve data science and analytics through replicable solutions for future reuse
Define best practices and develop a clear vision for productionalization
Contribute to a library of reusable algorithms with documented code

Requirements

Must be eighteen years of age or older
Must be legally permitted to work in the United States
Minimum 6+ years of experience in data science, machine learning engineering, AI engineering, software engineering, or MLOps, focused on production-ready AI solutions
2+ years of hands-on experience developing, deploying, evaluating, or supporting GenAI, LLM-based, or agentic AI solutions
Experience building agentic AI systems and multi-step workflows using tool calling, reasoning and planning, state and memory management, structured outputs, RAG/retrieval systems, embeddings, and API integration
Strong software engineering skills: Python, SQL, automated testing, containerization (Docker/Kubernetes), and cloud deployment (GCP preferred), with collaboration across Engineering, DevOps, and SRE partners
Expertise in foundational MLOps/LLMOps/AIOps practices: CI/CD automation, model/agent registries, versioning, automated testing, monitoring, automated retraining, rollback strategies, release management, and production support
Expertise in AI observability and governance: tracing, telemetry, automated alerting, anomaly detection, incident triage, eval harnesses, safety guardrails, model explainability, approval paths, fallback mechanisms, tool-use auditing, and cost/latency monitoring, including human-in-the-loop controls
Hands-on experience with agent orchestration frameworks, structured agent communication protocols (MCP, A2A), and Infrastructure-as-Code (IaC)
Ability to prototype lightweight tools or interfaces, evaluate technical feasibility, and document reusable architectural patterns
Continuous learning agility for emerging AI architectures, protocols, and operating models
Domain experience in merchandising, retail, ecommerce, supply chain, assortment planning, or space planning

Tools and technologies

Python, SQL
Docker, Kubernetes
GCP
CI/CD, CI/CD automation
RAG, retrieval systems, embeddings
API integration
MLOps, LLMOps, AIOps
IaC, MCP, A2A

Role details

Location: Atlanta, GA (onsite)
Minimum years of work experience: 5
Travel: typically requires overnight travel less than 10% of the time
Education: bachelor’s degree program or equivalent degree in a field of study related to the job
Reporting: this position reports to manager or above; 0 direct reports

Working conditions

Most of the time is spent sitting in a comfortable position, with frequent opportunity to move about
On rare occasions, there may be a need to move or lift light articles
Located in a comfortable indoor area; any unpleasant conditions would be infrequent and not objectionable

Competencies

Attracts Top Talent
Business Insight
Collaborates
Communicates Effectively
Cultivates Innovation
Customer Focus
Develops Talent
Directs Work
Drives Results
Nimble Learning
Optimizes Work Processes
Self-Development

View full job page →

19d ago

Data Scientist

FIS Global Atlanta, GA

Atlanta, GA

19d ago

Full time Artificial Intelligence Big Data Bigdata

Apply Now

Job Description

FIS Global is hiring a Data Scientist to help build and scale data-driven exploratory analysis, predictive models, and AI solutions across financial services business areas. This onsite role in Atlanta, GA focuses on supporting the full machine learning lifecycle and turning analytical results into practical, product-ready recommendations.

You will work on advanced analytics spanning model development through monitoring, with an emphasis on measurable business impact in payments and broader financial services.

What you’ll do

Participate in the end-to-end design, development, validation, deployment, and monitoring of advanced analytics, machine learning, and AI solutions.
Use data structures and algorithms to analyze, prepare, and assemble datasets from standard and novel data sources for analytical solutions.
Apply machine learning, predictive analytics, NLP, and emerging AI approaches such as GenAI and agentic techniques to address complex problems in the payments and financial services ecosystem.
Design and run experiments, hypothesis testing frameworks, and statistical analyses to evaluate business strategies, product enhancements, and operational improvements.
Establish and promote best practices across feature engineering, experimentation, model governance, and MLOps within the organization.
Stay current with industry trends in machine learning, AI, generative AI, and financial services analytics, and share relevant innovations with the team.

What you’ll bring

Master’s degree or higher in Mathematics, Computer Science, Engineering, Operations Research, Statistics, or a related quantitative field.
1-3 years of experience developing and deploying end-to-end machine learning, predictive analytics, and data science solutions in Payments, Banking, or Financial Services.
Strong proficiency in Python and SQL, with experience using big data tools such as Spark and PySpark as a plus.
Hands-on experience with data wrangling, feature engineering, and model development using Pandas, NumPy, scikit-learn, Matplotlib, Seaborn, or Plotly.
Proven experience building and deploying machine learning models in production or near-production settings.
Proficiency with data visualization and business intelligence tools, such as Tableau or equivalent.
Strong analytical thinking and problem-solving skills, including the ability to translate ambiguous business questions into rigorous analytical frameworks.
Ability to collaborate with product, engineering, and business stakeholders.

Technologies you may work with

Python, SQL, Spark, PySpark
Pandas, NumPy, scikit-learn
Matplotlib, Seaborn, Plotly
Tableau
NLP, GenAI, Agentic
MLflow, Model Registry, MLOps
Databricks (including Databricks platform), AWS
Transformer Models

Benefits

A voice in the future of fintech
Always-on learning and development
Collaborative work environment
Opportunities to give back
Competitive salary and benefits

Nice to have

Experience specifically within the Payments, Banking, or Financial Services industry.
Hands-on experience with the Databricks platform, including MLflow, Model Registry, collaborative notebooks, and MLOps workflows.
Experience deploying cloud-native machine learning solutions, particularly in AWS environments.
Familiarity with emerging advancements in Transformer Models and agentic AI.
Knowledge of model governance, regulatory compliance, and MLOps best practices in regulated financial services environments.

View full job page →

19d ago

Data Scientist - Decision Analytics

Home Depot / THD Atlanta, GA

Atlanta, GA

19d ago

Full time Advanced Analytics Analytics Big Data

Apply Now

Job Description

Shape analytics solutions that improve profitability, efficiency, and customer experience for Home Depot in Atlanta.

Responsibilities

Design and develop algorithms and models to generate business insights from large datasets
Serve as a technical lead on large data analytics project teams
Lead small projects and work independently on solution development
Apply advanced analytical methodologies, including appropriate selection, utilization, and interpretation
Develop approaches that incorporate business knowledge
Communicate insights and recommendations to technical and non-technical leaders, and business partners
Deliver recommendations in a confident manner to influence execution and implementation
Prepare reports, progress updates, and presentations for projects and solutions
Clearly explain the impact of recommendations to support alignment and appropriate rollout
Build trust and collaboration with internal customers and cross-functional teams
Partner with project teams and business stakeholders to define project goals
Stay current on key developments in data science, technical skill sets, and additional data sources
Contribute to continuous improvement by creating replicable solutions (for example, codified data products, documentation, process flowcharts) for reuse in future projects
Build and maintain a library of reusable algorithms; document developed code for future use
Develop trust and collaboration through effective cross-functional work

Requirements

Must be eighteen years of age or older
Must be legally permitted to work in the United States
Bachelor’s degree program or equivalent degree in a field related to the job
Minimum experience: 3 years

Technologies

Microsoft Excel
Power Point
Python
Google BigQuery
SQL
Tableau

Position Purpose

Support data science initiatives that drive business profitability, increased efficiencies, and improved customer experience
Use industry-leading analytical methodologies to work with large datasets and solve business problems
Document developed code into a library of reusable algorithms
Depending on the data science team, build knowledge in one or more specializations such as: optimization, computer vision, recommendation, search, or NLP

Work Location and Logistics

Location: Atlanta, GA (onsite)
Travel requirements: Typically overnight travel less than 10%

Working Conditions

Most time is spent sitting in a comfortable position with frequent opportunity to move about
On rare occasions, may need to move or lift light articles
Located in a comfortable indoor area; unpleasant conditions would be infrequent and not objectionable

Preferred Qualifications

Master’s in a quantitative field (Computer Science, Math, Statistics, etc.) or equivalent work experience
4+ years of experience in business intelligence and analytics
Working knowledge of Microsoft Excel and Power Point
Experience in a modern scripting language (preferably Python)
Proficient running queries against data (preferably Google BigQuery or SQL)
Proficient with data visualization software (preferably Tableau)
Proficient utilizing statistical techniques to identify key insights for business problem solving
Knowledgeable in prescriptive modeling such as optimization, computer vision, recommendation, search, or NLP
Demonstrated experience in predictive modeling, data mining, and data analysis

Competencies

Action Oriented: Takes on new opportunities and tough challenges with a sense of urgency, high energy, and enthusiasm
Business Insight: Applies knowledge of the business and the marketplace to advance organizational goals
Collaborates: Builds partnerships and works collaboratively with others to meet shared objectives
Communicates Effectively: Delivers multi-mode communication for different audiences
Customer Focus: Builds customer-centric solutions
Drives Results: Achieves results even under tough circumstances
Nimble Learning: Learns through experimentation using successes and failures
Optimizes Work Processes: Improves efficiency and continuously enhances processes
Plans and Aligns: Plans and prioritizes work aligned with organizational goals
Self-Development: Seeks growth through formal and informal development channels

View full job page →

19d ago

Data Scientist, Pricing (Forecasting & Deep Learning)

Home Depot / THD Atlanta, GA 🇺🇸 Remote

Atlanta, GA

19d ago

$90k - $160k/yr Full time Analytics Artificial Intelligence Business Analytics

Apply Now

Job Description

At Home Depot (THD), this Data Scientist role focuses on pricing optimization by leveraging future forecasted outcomes of price and promotions. You will apply advanced analytics and deep learning approaches to build models that support profitability, efficiency, and customer experience, while partnering across teams to turn insights into actionable recommendations.

This position is based in Atlanta, GA (remote) and supports work with large datasets using Python and SQL. The salary range is USD 90,000 - 160,000 per yearly, with a typical requirement of 3+ years of work experience.

What you’ll do

Design and develop algorithms and models that generate business insights from large datasets
Serve as a technical lead on large data analytics project teams
Lead small projects and independently develop solution approaches when needed
Select, apply, and interpret advanced analytical methodologies to address business problems
Communicate insights and recommendations clearly to technical and non-technical leaders and business partners
Present recommendations in a confident manner to influence execution
Prepare reports, updates, and presentations reflecting project or solution progress
Explain the impact of recommendations to support alignment and appropriate implementation
Incorporate business knowledge into the solution approach
Build trust and collaboration with internal customers and cross-functional teams
Work with project teams and business partners to define project goals
Continuously expand knowledge of data science developments, technical skill sets, and additional data sources
Support continuous improvement by developing replicable solutions such as codified data products, documentation, and process flowcharts
Build and maintain a library of reusable algorithms, with documented code for future use

Required qualifications

Must be eighteen years of age or older
Must be legally permitted to work in the United States
Completion of a bachelor’s degree or equivalent in a field related to the job
Minimum 3 years of work experience

Preferred qualifications

Past experience developing forecasting solutions and Deep Learning solutions in a professional environment
3+ years of experience in business intelligence and analytics
PhD in a quantitative field preferred (Computer Science, Math, Statistics, etc.)
Proficient in Python and SQL
Mastery using statistical techniques to identify insights that solve business problems
Demonstrated proficiency in predictive modeling such as optimization, forecasting, or recommendation
Demonstrated proficiency in predictive modeling, data mining, and data analysis

Working style and logistics

Typically requires overnight travel less than 10% of the time
Most of the time is spent sitting in a comfortable position, with frequent opportunity to move about; occasionally may require moving or lifting light articles
Located in a comfortable indoor area with infrequent, not objectionable unpleasant conditions

Team structure

This position typically reports to a Manager or above
Direct reports: 0

Compensation and benefits

Health care benefits
401K
ESPP
Paid time off
Success sharing bonus

View full job page →

21d ago

AI Engineer

Capgemini Atlanta, GA

Atlanta, GA

21d ago

$41 - $65/hr Contract Backend Developer Ai Agent Platform Artificial Intelligence

Apply Now

Job Description

Capgemini is seeking a hands-on AI Engineer in Atlanta, GA to enhance and optimize an existing AI platform built on Claude Sonnet and the Model Context Protocol (MCP). This is a contract role focused on improving AI agents, MCP tools and servers, enterprise integrations, and the overall quality, performance, security, and scalability of the platform.

Role Overview

You will work directly on MCP-based AI applications and agents, expanding core platform capabilities and strengthening end-to-end behavior. The role emphasizes improved context handling, reliable tool execution, and production readiness through monitoring, logging, security controls, and performance enhancements.

Responsibilities

Enhance and maintain MCP-based AI applications and agents
Develop and improve MCP servers, tools, and integrations
Integrate AI solutions with enterprise systems, APIs, databases, and knowledge repositories
Improve prompt engineering, context management, and response accuracy
Build and optimize RAG (Retrieval-Augmented Generation) solutions
Implement monitoring, logging, security controls, and performance improvements
Troubleshoot AI agent behavior, tool execution, and platform issues
Support deployment, testing, and continuous enhancement of AI capabilities

Required Qualifications

3+ years of software development experience using Python and/or TypeScript/Node.js
Hands-on experience building LLM / Generative AI applications
Strong understanding of MCP (Model Context Protocol), AI agents, and tool calling
Experience with Claude, OpenAI, or similar LLM platforms
Experience integrating APIs, databases, and enterprise applications
Knowledge of RAG, vector databases, embeddings, and prompt engineering
Strong debugging, problem-solving, and communication skills

Preferred Skills

Experience with LangChain, LangGraph, Semantic Kernel, or similar frameworks
Experience with AI observability, evaluation frameworks, and prompt optimization
Knowledge of security, authentication, and access control for AI applications
Experience deploying production-grade AI solutions

Technologies

Claude Sonnet, Model Context Protocol (MCP), TypeScript, Node.js, Python, LLM / Generative AI, RAG (Retrieval-Augmented Generation), vector databases, embeddings, LangChain, LangGraph, Semantic Kernel