- UpvoteDownvoteShare Job
- Suggest Revision
8+ years of experience in batch and streaming ETL using Spark, Python, Java, Snowflake or Databricks for Data Engineering or Machine Learning workloads. 5+ years orchestrating and implementing pipelines with workflow tools like Databricks Workflows, Apache Airflow, etc.
Full-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
- Suggest Revision
We use Apache Airflow, Python, and Apache Spark for ETL. For streaming data, we use Apache Kafka managed by a vendor and use Kafka Connect, Kafka Streams, and Spark Streaming for stream processing.
Full-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
- Suggest Revision
You Have: 8+ years of experience in batch and streaming ETL using Spark, Python, Java, Snowflake or Databricks for Data Engineering or Machine Learning workloads. 5+ years orchestrating and implementing pipelines with workflow tools like Databricks Workflows, Apache Airflow, etc 3+ years of experience prepping structured and unstructured data for data science models.
ExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
- Suggest Revision
Our main tech stack includes Snowflake, Apache Airflow, AWS cloud infrastructure (, Kinesis, Kubernetes/EKS, Lambda, Aurora RDS PostgreSQL), Python and Typescript. You’ll be part of a close-knit team of data engineers developing and maintaining a data platform built with automation and self-service in mind to support analytics and machine learning data products for the next generation of our that enable end-users to track, monitor and manage the health of their connected vehicles and deployed assets.
Full-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
- Suggest Revision
Experience with Databricks and/or Apache Spark a plus. 8+ years of experience in data architecture, data warehousing, business intelligence, data integration, data analysis, reporting, and/or machine learning.
ExpandApply NowActive JobUpdated 4 days ago - UpvoteDownvoteShare Job
- Suggest Revision
Some experience with cloud-based and on-prem data solutions (Apache Hadoop, Datastore, Firestore, Cloudera Data Platform, Big Query, Azure SQL, Cosmos DB, Red Shift, Apache Spark, ElastiCache, CloudSQL, Data Bricks, Snowflake, Apache Arrow, Apache Airflow, Flink.
ExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
- Suggest Revision
Within AWS, we’re focused on bringing that knowledge and capability to customers through three layers of the AI stack: 1) Frameworks and Infrastructure with tools like Apache MxNet and TensorFlow, 2) Machine Learning Platforms such as Amazon SageMaker for data scientists, and, 3) API-driven Services like Amazon Bedrock, Amazon Lex, Amazon Kendra, Amazon Transcribe, Amazon Comprehend, and Amazon Rekognition to quickly add intelligence to applications with simple API calls.
Full-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
- Suggest Revision
Deep understanding of cloud platforms (AWS, Google Cloud, Azure) and big data technologies (Apache Spark, Kafka). Implement advanced machine learning algorithms into practical, scalable applications that are integrated into broader systems.
ExpandApply NowActive JobUpdated Yesterday - UpvoteDownvoteShare Job
- Suggest Revision
Any level of experience with design and troubleshoot the complex Apache Spark jobs for building the Machine Learning data models for more than 100M Audience. Any level of experience with design and troubleshoot the complex Apache Spark jobs for building the Machine Learning data models for more than 100M Audience.
$150ExpandApply NowActive JobUpdated Yesterday - UpvoteDownvoteShare Job
- Suggest Revision
Broader knowledge of large dataset processing pipelines and distributed computing architectures (Apache Beam/Airflow, Spark/Hadoop architectures) Academic and/or experience in fields related to machine learning, deep learning and/or data science.
ExpandApply NowActive JobUpdated 3 days ago - UpvoteDownvoteShare Job
- Suggest Revision
Workflow scheduling tools such as Apache Airflow, windows scheduler, or Luigi. Working closely with Data Science and Analytics professionals, you will develop automated, streaming data pipelines for event capture, transformation, and feature extraction to assist the machine learning process.
$60 - $80 an hourExpandApply NowActive JobUpdated 1 month ago - UpvoteDownvoteShare Job
- Suggest Revision
Cloud and/or security certifications related to Cloud Architecture, Data Engineering, DevOps Engineering, DevSecOps, and Machine Learning is advantageous. Experience in building, configuring, operating and/or securing cloud infrastructure and applications in Azure or AWS, either with native cloud service provider capabilities or tools such as Terraform, Ansible, CloudFormation, Azure Resource Manager, Google Cloud Deployment Manager, or CloudBridge.
ExpandApply NowActive JobUpdated 13 days ago - UpvoteDownvoteShare Job
- Suggest Revision
AWS is looking for a Machine Learning Solutions Architect (ML SA), who will be the Subject Matter Expert (SME) for helping customers in the AMERICAS design solutions that leverage our GenAI services, including Amazon Bedrock, Amazon SageMaker, and Amazon Q. As part of the team, you will work closely with customers to enable large-scale use cases, design GenAI pipelines, and drive the adoption of AWS for the AI/ML platforms.
ExpandApply NowActive JobUpdated 11 days ago - UpvoteDownvoteShare Job
- Suggest Revision
Strong command of Apache Spark (3-5 years) This critical system not only requires ongoing production maintenance but also demands enhancements through integration with Machine Learning (Client) and Master Data applications.
ExpandApply NowActive JobUpdated 11 days ago - UpvoteDownvoteShare Job
- Suggest Revision
More than 10,000 organizations worldwide - including Comcast, Condé Nast, Grammarly, and over 50% of the Fortune 500 - rely on the Databricks Data Intelligence Platform to unify and democratize data, analytics and AI. Databricks is headquartered in San Francisco, with offices around the globe and was founded by the original creators of Lakehouse, Apache Spark, Delta Lake and MLflow.
ExpandApply NowActive JobUpdated 8 days ago
machine apache jobs in Chicago, IL
FEATURED BLOG POSTS
Why Work in Sales? 9 Reasons & Tips on Answering as an Interview Question!
Working in sales can be demanding and challenging, but it can also be gratifying. Sales is an excellent career with a clear path full of excitement and potential for growth. So, if you're contemplating careers and have wondered "why work in sales?", keep reading to determine if sales is a suitable role for you.
How to Fire an Employee
So… you've finally decided to let one of your employees go. Drafting the paperwork and corresponding with HR is the easy part, but knowing how to fire an employee is where things get complicated. In fact, it is one of the most challenging conversations to have in the workplace. However, it must be done, and it must be done with poise and tact. Not only should you keep your state law in mind, but you should also consider your former employee's wellbeing.
How Long Does it Take to Hear Back from a Job?
Are you applying for your very first job? Maybe you’re anticipating your termination from your current role and want to be proactive. Either way, waiting to hear back on your job application can be stressful. If time has passed since you applied, you may wonder how long does it take to hear back from a job. Well, the answer is... it depends.
How to Respond to a Recruiter Through Email? (Tips & Examples)
Rather than wading through an endless list of open roles, wouldn’t it be nice if relevant job opportunities come to you?
How to Reject a Candidate Professionally
When deciding on how to reject a candidate, your first question may be
How Does Salary Pay Work? (Compared to Hourly Pay)
At the bottom of each job advertisement, companies label a role as salaried or hourly. Both methods will get you paid (yay), but each in very different ways. So, it's essential to figure out how does salary pay work? While employees paid by the hour are paid based on how long they work, employers pay salaried employees a fixed amount.
The Quiet Quitting Phenomenon
The term, quiet quitting, was coined in 2009, but only now is it gaining traction as young Millennials and Gen Z workers are experiencing record levels of burnout. With the pandemic and the state of the economy, young employees are feeling the pressure. So, quiet quitting comes into effect when that pressure is exasperated by work stress and no managerial support.