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Data Engineer Relocation Jobs in Buford, GA (NOW HIRING)

No relocation is offered Overall Purpose: Translate business problems into actionable insights through a comprehensive workflow involving coding, data extraction, cleansing, feature engineering ...

In the assigned Job Role of Data Science Consultant 2, your Area Of Responsibility will be as below ... relocation and/or travel to work/project location. • Candidates authorized to work for any ...

Software engineering and/or Data Engineering background, especially in one of the major clouds ... Paid relocation is on us. Support, even from afar, with our remote assistance. Regular salary ...

Software engineering and/or Data Engineering background, especially in one of the major clouds ... Paid relocation is on us. Support, even from afar, with our remote assistance. Regular salary ...

... Engineering, Analytics, Security, and Product teams to ensure data is reliable, secure, governed ... This remote position is open to individuals who live in, or are open to relocating to, the ...

ML/AI Engineers

Atlanta, GA · On-site

$120 - $180/hr

... Learning Engineer, iOS and Android, data scientist, Developer solutions to industry giants ... Paid relocation is on us. * Support, even from afar, with our remote assistance. * Regular salary ...

Showing results 21-40

Data Engineer Relocation information

See Buford, GA salary details

$40.6K

$118.3K

$161.9K

How much do data engineer relocation jobs pay per year?

As of Sep 4, 2026, the average yearly pay for data engineer relocation in Buford, GA is $118,281.00, according to ZipRecruiter salary data. Most workers in this role earn between $104,400.00 and $125,400.00 per year, depending on experience, location, and employer.

What is a data engineer relocation?

A Data Engineer Relocation refers to the process of a data engineer moving to a new city, state, or country for a job opportunity. Often, companies offer relocation packages or assistance to help data engineers with the costs and logistics of moving. This can include covering moving expenses, temporary housing, and support for settling into a new location. Relocation is common in the tech industry due to the high demand for skilled data engineers in specific regions or at company headquarters.

What are the key skills and qualifications needed to thrive as a data engineer, and why are they important?

To thrive as a Data Engineer, you need strong skills in data modeling, ETL (Extract, Transform, Load) processes, and proficiency in programming languages such as Python or SQL, typically supported by a degree in computer science or a related field. Familiarity with big data platforms (like Hadoop or Spark), cloud services (such as AWS or Azure), and relevant certifications are highly valued. Excellent problem-solving, communication, and teamwork skills help you collaborate effectively and adapt to evolving data needs. These skills ensure robust data pipelines, reliable analytics, and support for organizational data-driven decision-making.

What are some common challenges data engineers face when relocating for a new position?

When relocating for a data engineering role, professionals often encounter challenges such as adapting to new data privacy regulations, integrating with local teams, and understanding company-specific data infrastructure. Adjusting to a different work culture and collaborating across time zones can also require flexibility and strong communication skills. Proactively seeking support from HR and technical onboarding resources can help ease the transition and ensure a smooth start in the new environment.

What is the difference between Data Engineer Relocation vs Data Engineer?

AspectData Engineer RelocationData Engineer
Required CredentialsBachelor's in CS, Data Science, or related field; experience with cloud platformsBachelor's or higher in CS, Data Science, or related; proficiency in SQL, Python, and ETL tools
Work EnvironmentTypically involves relocating to a new city or country; may include remote work optionsUsually based in an office or remote; focuses on data pipeline development
Employer & Industry UsageUsed by companies hiring for international or remote data roles requiring relocationCommon in tech, finance, healthcare industries for data infrastructure roles

In summary, Data Engineer Relocation involves moving to a new location for a data engineering role, often requiring additional logistical planning, while Data Engineer refers to the role itself, which can be based anywhere. Both roles share similar skills and credentials but differ mainly in the relocation aspect.

What cities near Buford, GA are hiring for Data Engineer Relocation jobs?

Cities near Buford, GA with the most Data Engineer Relocation job openings:

Infographic showing various Data Engineer Relocation job openings in Buford, GA as of August 2026, with employment types broken down into 85% Full Time, and 15% Contract. Highlights an 94% In-person, and 6% Remote job distribution, with an average salary of $118,281 per year, or $56.9 per hour.

Lead Data Scientist

AT&T

Atlanta, GA • On-site

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 7 days ago


Key responsibilities

  • Collect, clean, and preprocess data from various sources to ensure quality for analysis.

  • Create features, conduct exploratory data analysis, and develop machine learning models, including hyperparameter tuning and model evaluation.

  • Build visualizations and reports for stakeholders, and develop and implement generative AI models and techniques.


AT&T rating

7.4

Company rating: 7.4 out of 10

Based on 735 frontline employees who took The Breakroom Quiz

54th of 101 rated telecommunications companies


Job description

This position requires office presence of a minimum of 5 days per week and is only located in the location(s) posted. No relocation is offered

Overall Purpose: Translate business problems into actionable insights through a comprehensive workflow involving coding, data extraction, cleansing, feature engineering, exploratory data analysis, model creation and tuning, visualization, and deployment, leveraging statistical analysis, machine learning, and big data technologies to drive informed decision-making and innovation.
Key Roles and Responsibilities: Typical tasks may include, but are not limited to, the following:
Data Extraction and Preparation: Collect data from various structured and unstructured sources (datalakes, databases, data warehouses, on cloud, internal, external) and ensure its quality for analysis through cleaning and preprocessing. Designs, builds, and analyzes large (e.g. 100's of Terabytes or higher as technology advances) and complex data sets while thinking strategically about data use and data design. Tools can include
Coding Solutions, Algorithms and Feature Engineering: Create relevant features and conduct exploratory data analysis. Codes solutions following typical workflow; data extraction, cleansing, feature engineering, exploratory data analysis, model selection/creation, hyper-parameter tuning, model interpretation, model retraining, business process and/or system implementations, high level proof of concept and trials, visualization, deployment to production, post deployment ML ops monitoring/diagnosis/resolutions. Coding proficiency required in at least one data science language (Python, R, Scala, etc.), as well as expertise with modern ML packages and libraries (Spark, SciKitLearn, Pandas, PyTorch, TidyVerse, Tensorflow, Keras, Shiny, and/or AutoML tools).
Model Development, Deployment and Optimization: Build, evaluate, and optimize machine learning models through hyperparameter tuning. Implement models into production, continuously monitor their performance, and ensure they remain explainable and reliable to minimize model decay. Ability to develop custom Machine Learning (ML). Highly proficient in the full AI workflow such as (1) data extraction, cleansing, feature engineering, exploratory data analysis, model selection/creation, hyper-parameter tuning, model interpretation, model retraining and (2) Uses concepts like mlflow to log metrics. Well-versed in Interactive Development Environments (IDEs) such as Databricks Workspaces or Visual Studio Code. Proficiency in algorithm categories such as Supervised Learning, Unsupervised Learning, Optimization Algorithms, Deep Learning, AI-Computer Vision, Natural Language Processing, Deep Reinforcement Learning, Search Algorithms, and AI- Knowledge Graphs.
Visualization and Collaboration: Create visualizations and reports for stakeholders while working closely with cross-functional teams to align efforts with business objectives. Can utilize advanced coding methods to produce visualizations (e.g. ggplot, D3.js, etc.).
Generative AI: Develop and implement generative AI models, focusing on creating new content or augmenting existing data. Generative Models-Understanding of GANs (Generative Adversarial Networks), VAEs (Variational Autoencoders), and Transformers. Fine-Tuning-Techniques for adapting pre-trained models to specific tasks using smaller, task-specific datasets. Agentics-Understanding of agentic architecture, concepts and optimization of solutions. Prompt Engineering-Crafting effective prompts to guide generative models in producing desired outputs. Retrieval-Augmented Generation (RAG)-Combining generative models with retrieval systems to enhance performance and relevance. Text Generation-Proficiency in using models like GPT-3/4 for generating human-like text. Image Generation-Familiarity with tools like DALL-E and Stable Diffusion for creating images from text descriptions.
Job Contribution: An experienced professional, recognized as an expert, creatively resolving complex issues with broad and in-depth knowledge. Leads significant projects with strategic autonomy, influencing executive decisions. Mentors less experienced staff, implements long-term plans impacting the organization, and frequently collaborates with senior leadership. Supervisor: No
TCP Career Step Differentiator: Performs very complex data science work, builds complex business models, and makes recommendations that impact multiple organizations, lines of the business, etc.

Education/Experience: Master's degree (MS/MA) required from an accredited University in a Quantitative field of study such as Data Science, Math, Statistics, Engineering or Physics. 5+ years of related experience. Certification is required in some areas.

Relevant Material Job Duties for which Criminal History may have a direct adverse, and negative relationship potentially resulting in the withdrawal of the Conditional Offer of Employment
Contact with Customers/Candidates/Clients
Safety Sensitivity (Vehicle/Tool/Machine Operation - if applicable)
Handling/Proximity to Sensitive Information

Our Lead Data Scientist jobs earn between $160,900.00 - $270,400.00 USD Annual. Not to mention all the other amazing rewards that working at AT&T offers. Individual starting salary within this range may depend on geography, experience, expertise, and education/training.

Joining our team comes with amazing perks and benefits:

  • Medical/Dental/Vision coverage
  • 401(k) plan
  • Tuition reimbursement program
  • Paid Time Off and Holidays (based on date of hire, at least 23 days of vacation each year and 9 company-designated holidays)
  • Paid Parental Leave
  • Paid Caregiver Leave
  • Additional sick leave beyond what state and local law require may be available but is unprotected
  • Adoption Reimbursement
  • Disability Benefits (short term and long term)
  • Life and Accidental Death Insurance
  • Supplemental benefit programs: critical illness/accident hospital indemnity/group legal
  • Employee Assistance Programs (EAP)
  • Extensive employee wellness programs
  • Employee discounts up to 50% off on eligible AT&T mobility plans and accessories, AT&T internet (and fiber where available) and AT&T phone

Weekly Hours:

40

Time Type:

Regular

Location:

Atlanta, Georgia, Dallas, Texas, El Segundo, California

Salary Range:

$160,900.00 - $270,400.00

AT&T and its subsidiaries are committed to equal employment opportunity. All hiring, promotion, and other employment decisions remain merit-based and free from discrimination on the basis of race, color, religion, religious creed, national origin, ancestry, age, sex, sexual orientation, gender, gender identity, gender expression, physical disability, mental disability, pregnancy, medical condition, genetic information, marital status, citizenship status, military status, veteran status, or any other characteristic protected by federal, state, or local laws. In addition, AT&T will provide reasonable accommodations to qualified individuals with disabilities. AT&T is a fair chance employer and does not initiate a background check until an offer is made. Click here to learn more or request an application accommodation here.


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