1

Google Data Science Jobs in Alabama (NOW HIRING)

... Engineer, Google Professional Cloud Architect, GCP Data Engineer Microsoft Azure Solutions ... science workflows is a plus - Knowledge of data governance and data security practices ...

... and Information Science, Systems Engineering, Electrical Engineering, Chemical Engineering ... Engineer, Google Professional Cloud Architect, GCP Data Engineer Microsoft Azure Solutions ...

Cloud Developer Mid

Huntsville, AL · Hybrid

$58.50 - $80/hr

... Azure, or Google Cloud. * Strong knowledge of containerization (e.g., Docker, Kubernetes ... Data Science, and Programmatic support. We offer our clients nimble, unique, and value focused ...

Cloud Developer Mid

Huntsville, AL · On-site

$58.50 - $80/hr

... Azure, or Google Cloud. * Strong knowledge of containerization (e.g., Docker, Kubernetes ... Data Science, and Programmatic support. We offer our clients nimble, unique, and value focused ...

Cloud Developer Mid

Huntsville, AL · On-site

$58.50 - $80/hr

... Azure, or Google Cloud. * Strong knowledge of containerization (e.g., Docker, Kubernetes ... Data Science, and Programmatic support. We offer our clients nimble, unique, and value focused ...

Data Analysis Tutor

Montgomery, AL · Remote

$18 - $40/hr

Adapts instruction using Excel, Google Sheets, SQL platforms, and visualization tools like Tableau ... science to create personalized learning experiences. Through 1-on-1 Online Tutoring, students ...

Data Analysis Tutor

Birmingham, AL · Remote

$18 - $40/hr

Adapts instruction using Excel, Google Sheets, SQL platforms, and visualization tools like Tableau ... science to create personalized learning experiences. Through 1-on-1 Online Tutoring, students ...

Data Analysis Tutor

Tuscaloosa, AL · Remote

$18 - $40/hr

Adapts instruction using Excel, Google Sheets, SQL platforms, and visualization tools like Tableau ... science to create personalized learning experiences. Through 1-on-1 Online Tutoring, students ...

Data Analysis Tutor

Huntsville, AL · Remote

$18 - $40/hr

Adapts instruction using Excel, Google Sheets, SQL platforms, and visualization tools like Tableau ... science to create personalized learning experiences. Through 1-on-1 Online Tutoring, students ...

Cloud Developer SME

Huntsville, AL · On-site

$58.50 - $80/hr

... Azure, or Google Cloud. * Strong knowledge of containerization (e.g., Docker, Kubernetes ... Data Science, and Programmatic support. We offer our clients nimble, unique, and value focused ...

Cloud Developer SME

Huntsville, AL · On-site

$58.50 - $80/hr

... Azure, or Google Cloud. * Strong knowledge of containerization (e.g., Docker, Kubernetes ... Data Science, and Programmatic support. We offer our clients nimble, unique, and value focused ...

Cloud Developer SME

Huntsville, AL · Hybrid

$58.50 - $80/hr

... Azure, or Google Cloud. * Strong knowledge of containerization (e.g., Docker, Kubernetes ... Data Science, and Programmatic support. We offer our clients nimble, unique, and value focused ...

next page

Showing results 1-20

Google Data Science information

Can data scientists make $300k?

Data scientists, including those working at Google, can earn $300,000 or more annually, especially with senior roles, extensive experience, advanced skills in machine learning and big data tools, and in high-cost-of-living areas. Compensation often includes base salary, bonuses, and stock options, which contribute to total earnings at this level.

What are the key skills and qualifications needed to thrive in the Google Data Science position, and why are they important?

To thrive as a Google Data Science professional, you need a strong foundation in statistical analysis, machine learning, and data manipulation, often supported by a degree in a quantitative field such as computer science, statistics, or mathematics. Proficiency in programming languages like Python or R, experience with large-scale data processing tools (such as SQL, TensorFlow, or BigQuery), and familiarity with cloud-based platforms are commonly required. Excellent problem-solving, communication, and collaboration skills help set candidates apart in effectively translating complex data insights to varied stakeholders. These capabilities are crucial for driving impactful, data-driven decisions within cross-functional teams at Google.

How much does Google pay a Data Scientist?

Google Data Scientists typically earn a base salary ranging from $120,000 to $180,000 annually, with total compensation often including bonuses and stock options that can increase overall earnings. Compensation varies based on experience, location, and skill level, with advanced skills in machine learning and data analysis tools being highly valued.

Is 40 too late for data science?

Age is not a barrier to becoming a data scientist, including at age 40. Success in data science depends on skills, experience, and continuous learning of tools like Python, R, and SQL, rather than age. Many professionals transition into data science later in their careers and find opportunities with relevant certifications and a strong portfolio.

What is a Google Data Science job?

A Google Data Science job involves analyzing large datasets to provide insights and drive data-informed decisions. Data scientists at Google apply statistical modeling, machine learning, and analytical techniques to solve complex problems in products like Search, Ads, YouTube, and Cloud. They work closely with engineers, product managers, and business teams to develop data-driven solutions. Strong coding skills in Python or SQL, experience with big data tools, and a solid foundation in statistics are essential for this role.

What types of projects do Google Data Science professionals typically work on?

Google Data Science professionals engage in a wide variety of impactful projects, such as optimizing algorithms for product recommendations, improving user experiences through data-driven insights, and developing predictive models to inform business strategies. They often work closely with product managers, engineers, and designers to translate complex data findings into actionable solutions. The work environment is highly collaborative and fast-paced, with opportunities to contribute to innovative initiatives across different Google products and services. This dynamic setting allows data scientists to continuously expand their skill sets and take on new challenges, fostering both personal and professional growth.

What is the average salary for a Data Scientist at Google?

The average salary for a Data Scientist at Google is approximately $120,000 to $150,000 per year, depending on experience, location, and level. Senior roles or those with specialized skills in machine learning and data analysis can earn higher compensation, often including bonuses and stock options.
What are popular job titles related to Google Data Science jobs in Alabama? For Google Data Science jobs in Alabama, the most frequently searched job titles are:
What job categories do people searching Google Data Science jobs in Alabama look for? The top searched job categories for Google Data Science jobs in Alabama are:
Infographic showing various Google Data Science job openings in Alabama as of June 2026, with employment types broken down into 1% As Needed, 89% Full Time, 7% Part Time, 1% Temporary, and 2% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution.
Data Engineer - Manager

Data Engineer - Manager

Pwc

Birmingham, AL • On-site

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 22 days ago


PwC rating

8.3

Company rating: 8.3 out of 10

Based on 75 frontline employees who took The Breakroom Quiz

20th of 57 rated business consultants


Job description

Industry/Sector

Not Applicable

Specialism

Data, Analytics & AI

Management Level

Manager

Job Description & Summary

At PwC, our people in data and analytics engineering focus on leveraging advanced technologies and techniques to design and develop robust data solutions for clients. They play a crucial role in transforming raw data into actionable insights, enabling informed decision-making and driving business growth.
In data engineering at PwC, you will focus on designing and building data infrastructure and systems to enable efficient data processing and analysis. You will be responsible for developing and implementing data pipelines, data integration, and data transformation solutions.
Enhancing your leadership style, you motivate, develop and inspire others to deliver quality. You are responsible for coaching, leveraging team member's unique strengths, and managing performance to deliver on client expectations. With your growing knowledge of how business works, you play an important role in identifying opportunities that contribute to the success of our Firm. You are expected to lead with integrity and authenticity, articulating our purpose and values in a meaningful way. You embrace technology and innovation to enhance your delivery and encourage others to do the same.
Examples of the skills, knowledge, and experiences you need to lead and deliver value at this level include but are not limited to:
Analyse and identify the linkages and interactions between the component parts of an entire system.
Take ownership of projects, ensuring their successful planning, budgeting, execution, and completion.
Partner with team leadership to ensure collective ownership of quality, timelines, and deliverables.
Develop skills outside your comfort zone, and encourage others to do the same.
Effectively mentor others.
Use the review of work as an opportunity to deepen the expertise of team members.
Address conflicts or issues, engaging in difficult conversations with clients, team members and other stakeholders, escalating where appropriate.
Uphold and reinforce professional and technical standards (e.g. refer to specific PwC tax and audit guidance), the Firm's code of conduct, and independence requirements.
As part of the Data and Analytics Engineering team you can design and implement thorough data architecture strategies that meet current and future business needs. As a Manager you can lead the development of data models, support compliance with data governance policies, and collaborate with business stakeholders to translate data requirements into technical solutions. You can also build and enhance ETL/ELT pipelines, manage data warehouses and data lakes, and implement data security practices.
Responsibilities
- Design and implement thorough data architecture strategies
- Lead the development of data models
- Achieve compliance with data governance policies
- Collaborate with business stakeholders to translate data requirements
- Build and enhance ETL/ELT pipelines
- Manage data warehouses and data lakes
- Implement data security leading practices
- Foster a culture of data-driven decision making
What You Must Have
- Bachelor's Degree in Management Information Systems, Computer and Information Science, Systems Engineering, Electrical Engineering, Chemical Engineering, Industrial Engineering, Mathematics, Statistics, or Mathematical Statistics
- 5 years of experience
What Sets You Apart
- Certification in Cloud Platforms [e.g., AWS Solutions Architect, AWS Data Engineer, Google Professional Cloud Architect, GCP Data Engineer Microsoft Azure Solutions Architect, Azure Data Engineer Associate, or Snowflake Core, Snowflake Databricks Data Engineer Associate] is a plus
- Designing and implementing thorough data architecture strategies that meet the current and future business needs
- Developing and documenting data models, data flow diagrams, and data architecture guidelines
- Verifying data architecture is compliant with data governance and data security policies
- Collaborating with business stakeholders to understand their data requirements and translate them into technical solutions
- Evaluating and recommending new data technologies and tools to enhance data architecture
- Building, maintaining, and improving ETL/ELT pipelines for data ingestion, processing, and storage across batch and real-time data processing
- Building, maintaining, and improving Data Quality rules leveraging DQ tools and/or other ETL/ELT tools
- Developing and deploying scalable data storage solutions using AWS, Azure and GCP services such as S3, Amazon RDS, DynamoDB, Azure Data Lake Storage, Azure Cosmos DB, Azure SQL DB, GCP Cloud Storage etc.
- Implementing data integration solutions using AWS Glue, AWS Lambda, Azure Data Factory, Azure Functions, GCP Functions, GCP Dataproc, Dataflow and other relevant services
- Designing and managing data warehouses and data lakes, verifying data is organized and accessible
- Monitoring and troubleshooting data pipelines, data warehouses and workflows to verify data quality, system reliability, performance and cost management
- Implementing IAM roles and policies to manage access and permissions within AWS, Azure, GCP
- Use AWS CloudFormation, Azure Resource Manager templates, Terraform for infrastructure as code (IaC) deployments
- Use AWS, Azure and GCP DevOps services to build and deploy DevOps pipelines
- Implementing data security practices using AWS, Azure, GCP, Snowflake or Databricks
- Improving Cloud resources for cost, performance, and scalability
- Proficiency in SQL and experience with relational databases
- Proficient in programming languages such as Python, Java, or Scala
- Familiarity with big data technologies like Hadoop, Spark, or Kafka is a plus
- Experience with machine learning and data science workflows is a plus
- Knowledge of data governance and data security practices
- Demonstrating analytical, problem-solving, and communication skills
- Having the ability to work independently and as part of a team in a fast-paced environment
- Applying modern, cloud-based technology skills, ability to research emerging trends, analyst publications, and adoption of modern technologies in solution architectures
- Collaborating and contributing as a team member: understanding personal and team roles, contributing to a positive working environment by building proven relationships with team members, proactively seeking guidance, clarification and feedback
- Prioritizing and handling multiple tasks, researching and analyzing pertinent client, industry and technical matters, utilizing problem-solving skills, and communicating effectively in written and verbal formats to various audiences (including various levels of management and external clients) in a professional business environment
- Coaching and collaborating with associates who assist with this work, including providing coaching, feedback and guidance on work performance

Travel Requirements

Up to 60%

Job Posting End Date

The salary range for this position is: $99,000 - $232,000. Actual compensation within the range will be dependent upon the individual's skills, experience, qualifications and location, and applicable employment laws. All hired individuals are eligible for an annual discretionary bonus. PwC offers a wide range of benefits, including medical, dental, vision, 401k, holiday pay, vacation, personal and family sick leave, and more. To view our benefits at a glance, please visit the following link: https://pwc.to/benefits-at-a-glanceAs PwC is anequal opportunity employer, all qualified applicants will receive consideration for employment at PwC without regard to race; color; religion; national origin; sex (including pregnancy, sexual orientation, and gender identity); age; disability; genetic information (including family medical history); veteran, marital, or citizenship status; or, any other status protected by law.PwC does not intend to hire experienced or entry level job seekers who will need, now or in the future, PwC sponsorship through the H-1B lottery, except as set forth within the following policy: https://pwc.to/H-1B-Lottery-Policy.Learn more about how we work: https://pwc.to/how-we-workFor only those qualified applicants that are impacted by the Los Angeles County Fair Chance Ordinance for Employers, the Los Angeles' Fair Chance Initiative for Hiring Ordinance, the San Francisco Fair Chance Ordinance, San Diego County Fair Chance Ordinance, and the California Fair Chance Act, where applicable, arrest or conviction records will be considered for Employment in accordance with these laws. At PwC, we recognize that conviction records may have a direct, adverse, and negative relationship to responsibilities such as accessing sensitive company or customer information, handling proprietary assets, or collaborating closely with team members. We evaluate these factors thoughtfully to establish a secure and trusted workplace for all.Applications will be accepted until the position is filled or the posting is removed, unless otherwise set forth on the following webpage. Please visit this link for information about anticipated application deadlines: https://pwc.to/us-application-deadlines

What PwC employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom