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Data Engineer Relocation Jobs in Georgia (NOW HIRING)

AT and T

Principal Data/AI Engineering

Atlanta, GA · On-site

$155K - $261K/yr

No relocation is offered. At AT&T, we empower leaders to drive change in a fast-evolving, connected ... As a Principal Data/AI Engineering your tasks may include, but are not limited to, the following:

AT&T

Principal Data/AI Engineering

Alpharetta, GA · On-site

$155K - $261K/yr

No relocation is offered. At AT&T, we empower leaders to drive change in a fast-evolving, connected ... As a Principal Data/AI Engineering your tasks may include, but are not limited to, the following:

AT&T

Principal Data/AI Engineering

Atlanta, GA · On-site

$155K - $261K/yr

No relocation is offered. At AT&T, we empower leaders to drive change in a fast-evolving, connected ... As a Principal Data/AI Engineering your tasks may include, but are not limited to, the following:

Mondo

Principal Engineer, SFMC

Atlanta, GA · Hybrid

... relocation assistance up to $20,000; additional benefits Visa Sponsorship: Not eligible for visa ... Establish and maintain best practices for data hygiene, synchronization, and governance across ...

Mondo

Principal Engineer, SFMC

Atlanta, GA · On-site

... relocation assistance up to $20,000; additional benefits Visa Sponsorship: Not eligible for visa ... Establish and maintain best practices for data hygiene, synchronization, and governance across ...

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Data Engineer Relocation information

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 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 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 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 popular job titles related to Data Engineer Relocation jobs in Georgia? For Data Engineer Relocation jobs in Georgia, the most frequently searched job titles are:
What job categories do people searching Data Engineer Relocation jobs in Georgia look for? The top searched job categories for Data Engineer Relocation jobs in Georgia are:
What cities in Georgia are hiring for Data Engineer Relocation jobs? Cities in Georgia with the most Data Engineer Relocation job openings:
Data Engineer Relocation jobs near you
Data Scientist - AI/ML (Atlanta, GA)

Data Scientist - AI/ML (Atlanta, GA)

Spartan Technologies, Inc.

Atlanta, GA • On-site

Full-time

Re-posted 5 days ago

Job description

We are seeking a Data Scientist who will be responsible for supporting predictive analytic initiatives that empower business decisions and is available for a direct hire/permanent role. The locations for this role are Atlanta, GA, FL, KS, LA, MS, OK, PA or TX. We are not seeking candidates who require relocation at this time. Also, we will consider candidates who are residents in Texas as well. This is a remote position.
Oil or Gas Industry experience is highly preferred for this role.
This role applies industry-leading methodologies for working with large datasets to extract meaningful business insight and creatively solve business problems. This role will apply advanced methods and algorithms for identifying trends, predicting outcomes, and alerting the business to potential issues. Additionally, the Data Scientist is expected to present insights and recommendations to non-technical audiences and explain the benefits and impacts of the recommended solutions.
The Data Scientist will be a key member of the Data and Analytics Platform Services team. This role will create analytical models and datasets while working with a Data Engineer to develop code for extracting data from source systems, which will include the Relational Enterprise Data Warehouse, Operational Data Store, and Azure Data Lake Store. The ideal candidate will also be passionate about developing machine learning models using Azure Databricks and/or Azure ML Studio, or a comparable platform for operationalizing Machine Learning workloads.
Responsibilities:
• Engage with business partners and stakeholders to understand business problems and translate them into data science solutions.
• Coordinate and collaborate with data science, data engineering, analytic engineering, and other resources to achieve business goals.
• Work cross-functionally with finance, operations, and field engineering teams on opportunities for improved insights.
• Lead and contribute to the end-to-end development and deployment of predictive and prescriptive models.
• Explore large datasets using modeling, analysis, and visualization techniques.
• Communicate results, analyses, and methodologies to technical and non-technical senior level stakeholders.
• Ability to mentor, coach, and lead others.
• Contribute to and help build ML/AI vision to support business strategy.
Required Knowledge, Skills, Abilities (Qualifications):
• Degree in Data Science, Machine Learning, Applied Mathematics/Statistics, or a related field.
• 7 years of experience applying data science, AI/machine learning, and analytics techniques to business problems.
• Experience leading data science projects.
• Experience with supervised and unsupervised machine modeling techniques, with a focus on time-series forecasting.
• Experience solving real-world problems using programming languages such as SQL, Spark, and Python, and deploying solutions to enterprise systems.
• Excellent strategic thinking, communication, collaboration, and problem-solving skills, including working with and articulating results to senior business stakeholders.
Preferred Knowledge, Skills, Abilities:
• It is considered a plus to have knowledge and working experience in any of the following areas: Oil and Gas use cases for predictive analytics.
Travel Requirements: 10%
Position Location: Open

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