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Remote Aws Data Engineer Jobs in San Ramon, CA (NOW HIRING)

6sense

Sr. Software Engineer

San Francisco, CA · Remote

$179K - $263K/yr

... Big Data area Nice to Have Skills * Experience with Django framework * Exposure to AWS ... remote Notice of Collection and Use of Personal Information for California Residents: California ...

Philo

Director of Data Engineering

San Francisco, CA · On-site +1

$298K/yr

To complete our work, we build on modern tools including AWS-native services, dbt, Segment ... San Francisco, CA, Brooklyn, NY, Cambridge, MA, or remote within the U.S. Compensation: Includes ...

eAI

Head of AI & Data

San Francisco, CA · On-site +1

$134K - $162K/yr

Work closely with engineering to operationalize AI features at scale Financial Use Cases & Domain ... Exposure to scalable cloud data/ML infrastructure (AWS, GCP, etc.) * Experience building systems ...

DataHub

Customer Centric Engineer

Palo Alto, CA · On-site +1

DataHub is an AI & Data Context Platform adopted by over 3,000 enterprises, including Apple, CVS ... Solid understanding of networking, system architectures, and cloud platforms (AWS, Azure, GCP)

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Remote Aws Data Engineer information

See San Ramon, CA salary details

$49.7K

$145K

$198.4K

How much do remote aws data engineer jobs pay per year?

As of Jul 16, 2026, the average yearly pay for remote aws data engineer in San Ramon, CA is $144,961.00, according to ZipRecruiter salary data. Most workers in this role earn between $128,000.00 and $153,700.00 per year, depending on experience, location, and employer.

What is a Remote AWS Data Engineer?

A Remote AWS Data Engineer is a professional who designs, builds, and maintains data pipelines and architectures using Amazon Web Services (AWS) infrastructure, while working remotely. They are responsible for tasks such as data ingestion, transformation, storage, and ensuring data quality and security. AWS Data Engineers often work with services like Amazon S3, Redshift, Glue, Lambda, and EMR to enable scalable and efficient data processing. Their role is crucial in helping organizations manage and analyze large datasets in the cloud. Working remotely allows them to collaborate with teams from different locations using online tools and platforms.

What is the difference between Remote Aws Data Engineer vs Remote Cloud Data Engineer?

AspectRemote Aws Data EngineerRemote Cloud Data Engineer
CertificationsAWS Certified Data Analytics, AWS Certified Data Analytics - SpecialtyCloud certifications (AWS, Azure, GCP), relevant data certifications
Work EnvironmentPrimarily AWS cloud platform, data pipelines, ETL processesMultiple cloud platforms, data integration across services
Industry UsageTech, finance, healthcare using AWS infrastructureVaries across industries using multiple cloud providers
Search & Comparison IntentHigh overlap in skills, AWS-specific toolsBroader cloud skills, multi-platform focus

The Remote Aws Data Engineer specializes in AWS cloud services, focusing on data pipelines and analytics within the AWS ecosystem. In contrast, the Remote Cloud Data Engineer works across multiple cloud platforms, requiring broader cloud skills. Both roles involve data engineering but differ in platform expertise and certifications.

How does a remote AWS Data Engineer typically collaborate with cross-functional teams?

As a remote AWS Data Engineer, you'll often work closely with data scientists, analysts, and software engineers to design and maintain scalable data pipelines in the cloud. Collaboration usually happens through virtual meetings, cloud-based project management tools, and shared documentation platforms. Clear communication and proactive updates are essential to ensure everyone stays aligned, especially when troubleshooting data issues or implementing new features. Building strong working relationships remotely can be challenging, but most organizations support this with regular check-ins and team collaboration channels.

What are the key skills and qualifications needed to thrive as a Remote AWS Data Engineer, and why are they important?

To thrive as a Remote AWS Data Engineer, you need strong expertise in data engineering concepts, programming (such as Python or Scala), and experience with AWS cloud services like S3, Redshift, and Glue, typically supported by a relevant degree or AWS certification. Proficiency with ETL tools, data pipeline frameworks (e.g., Apache Airflow), and AWS-specific technologies is essential. Strong problem-solving abilities, communication skills, and self-motivation are crucial soft skills for remote collaboration and project delivery. These capabilities ensure scalable, secure, and efficient data solutions in distributed, cloud-based environments.
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Remote Aws Data Engineer jobs near you
Data Science

Data Science

Adidev Technologies Inc

San Francisco, CA • Remote

Full-time

Re-posted 25 days ago

Job description

Adidev Technologies Inc 

www.adidevtechnologies.com

URGENT HIRE - HIRING PROCESS - 24-48 HOURS!

Adidev Technologies is seeking 1-2 yrs of relevant experience in Data Science. A project can last anywhere from 6 months to 18 months. Salary varies depending on experience, and we are in search of candidates looking to start as soon as possible. Excellent written and oral communication are required as is the ability to work well in a team environment.

If you are looking for a new challenge and are ready to make an impact on a growing team, then this will be a perfect fit. As a Data Scientist/Data Science Specialist for Adidev Technologies Inc., you will be enhancing and debugging large-scale applications for one of our well-known clients.

Adidev Technologies is a growing software consulting company that is constantly expanding. As we are working with renowned clients and ready to take on new ones, we are seeking brilliant software engineers. Not only do we offer a great team to work with, but we also offer you an opportunity to make an immediate impact and get rewarded accordingly

 

Job Description

  • Demonstrated experience using machine learning, deep learning, statistical methodology, and simulation/optimization modeling in geospatial, network topography, recommendation systems, environmental systems, and/or agronomic problems.
  • Strong foundation in Python programming in a cloud environment.
  • Strong quantitative abilities, distinctive problem-solving, and excellent analysis skills
  • Expertise in data wrangling using SQL,
  • Practical knowledge and experience with cloud-computing systems and platforms, including the routine deployment of pipelines through Kubernetes
  • Fluency in querying/extracting/aggregating data via SQL scripting.
  • Extract, load and transform data (ETL) from structured and unstructured sources
  • Apply Natural Language Processing and Computer Vision to solve business use cases,
  • Strong skills in scientific data analyses, modeling, visualization and communication of results.
  • Knowledge of Python libraries (NumPy, Pandas, SciKit-Learn, TensorFlow, PyTorch), Spacy, MongoDB, PostgreSQL, Flask, streamlet and a good knowledge of data pipelines construction
  • Ph.D., M.S. or B.S. in Computer Science, Computational Physics, Operations Research, Geospatial Sciences, Remote Sensing Science, Environmental Sciences, Computational Astronomy or related scientific discipline


Must  have 

  • Understanding of various machine learning algorithms (e.g. SVM, Random Forests, Gradient Boosting, Log-Log regression, XGBoost, Lasso, Ridge, Clustering techniques, Neural Networks and others)
  • Regression (e.g. ? Linear/Logistic/MNL/Mixed Effects/Regularization)
  • Classification (K-means, Hierarchical, Latent Class, DBScan, SVM)
  • Dimension Reduction techniques (Principal Component analysis, Singular Value Decomposition etc.)
  • Optimization (Linear programming, Stochastic Gradient Descent, Genetic Algorithm etc.)
  • Experience with neural network approaches to text classification CNN, RNN, LSTM,Keras
  • Machine Learning algorithms? Neural Networks, Naïve Bayes, Bagging & Boosting, Random Forest
  • Distributed computing tools and cloud technology (AWS)

QUALIFICATIONS

  • Degree in Data Science, Computer Science, Engineering, Math, or Statistics preferred

  • At least 2 yrs of relevant experience in Data Science


SKILLS

  • SQL, statistical modeling, Feature engineering, Data visualization, Deploying models to production, Python programming, AWS, Domains(Healthcare/ Manufacturing/ Marketing/ Financial/ Telecommunication), powerbi/tableau, data warehouse

Benefits

  • Competitive Salary

  • Paid Relocation

  • Remote Support

  • Guaranteed Regular Salary Reviews

  • Job Type: W2 or Contract 1099 (full-time - 40 hours)

Employment Type: FULL_TIME

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