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Expertise in Databricks, Apache Spark, and big data technologies. Architect and implement big data processing solutions leveraging Apache Spark for ETL, data transformation, and machine learning workflows.
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Knowledge of big data processing and analytics tools on gcp like bigquery dataproc experience in big data processing and analytics tools on gcp like bigquery. Our areas of expertise include application modernization ecommerce uxui design product strategy data analytics and artificial intelligence.
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Hands on experience with modern cloud data warehouse and engineering for one or more of the following cloud providers - GCP (Big Query, Vertex, Cognitive Services), Snowflake, Azure (Synapse, Dynamo, Cosmos, Azure ML, Power BI), AWS (Redshift, Sage maker), Tableau;Possessing a certification(s) in one of the following is a big plus – GCP/AWS/Azure/ data or ML engineering.
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Experience with Azure Synapse, Databricks, ADLS Gen 2, Google Analytics, Firebase, Big Query, Event Hubs, Kafka, Salesforce, SAP, and CDP platforms. Data Evangelist: Promote data product adoption through training and webinars.
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Familiarity with Big Data is preferred. Propose new database architecture and support data migration from an existing Legacy system to a new structureCreate source-to-target mapping documents to transform the source data into the target warehouse and test final transformations.
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Experience building and managing production-grade data pipelines using tools such as Airflow, dbt, DataHub, MLFlow. Youll 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 T3 Fleet that enable end-users to track, monitor and manage the health of their connected vehicles and deployed assets.
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Experience with Data Ops (VPCs, cluster management, permissions, Databricks configurations, Terraform) in Cloud Computing environments (e.g., AWS, Azure, GCP) and associated cloud data platforms, cloud data warehouse technologies (Snowflake/Redshift), and Advanced Analytical platforms (e.g., Dataiku and Databricks.
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Alteryx, Banking, Business, Critical Thinking, Data Acquisition, Data Analysis, Data Management, Data Operations, Data Quality, Decision Making, Financial Products, Leadership, Management Reporting, Microsoft Power BI, People Management.
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Knowledge of Statistics, Gen AI, LLM, Python, Computer Vision, data visualization tools. We want Data Science/Machine learning/Data Analyst and Java Full stack candidates. Currently, We are looking for entry-level software programmers, Java full-stack developers, Python/Java developers, Data analysts/ Data Scientists, and Machine Learning engineers for full-time positions with clients.
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The Far Horizons program is currently doing fieldwork using two main instrument sets designed and built at the Adler: the GONet camera system, which collects all-sky nighttime environment data in the field, and the NITELite system, which is a high-altitude balloon-borne camera system that collects regional scale night-time images from the stratosphere.
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Experience with Snowflake/BigQuery, Google Dataproc/Databricks or any big data frameworks on Spark. Enable functionality to support analysis, model optimization, statistical testing, model versioning, deployment and monitoring of model and data.
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As a Data Scientist at Capital One, you'll be part of a team that's leading the next wave of disruption at a whole new scale, using the latest in computing and machine learning technologies and operating across billions of customer records to unlock the big opportunities that help everyday people save money, time and agony in their financial lives.
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You should have a Data Engineering Transformation Tools: Familiarity with data integration tools Cloud Composer (based on Apache Airflow) , Dataflow , Cloud Run. Must have Programming Languages/Infrastructure as Code/ Code Management : Strong knowledge of languages commonly used in data engineering, such as Python, SQL ,Terraform, CI/CD , Git flows, Attunity , AutoSys.
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Apache Hadoop or Apache Spark (for big data processing) Data Warehousing (e.g., AWS Redshift, Google BigQuery) Natural Language Processing (NLP) Tools and Frameworks (e.g., Hugging Face, AWS Comprehend Medical for extracting insights from clinical text data.
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Chicago is the place to be in all seasons, and it’s no surprise that it was voted “Best Big City in the.” All year, sports enthusiasts can cheer for the Bulls, Bears, Blackhawks, White Sox, Cubs, or Fire.
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big data jobs Company: Nugget Market in Chicago, IL
FEATURED BLOG POSTS
Virtual Reality Job Interviews
With the advent of desktop computers, the arduous task of scouring through weekly job classifieds became a thing of the past. The mid-1990s brought about a new era where job seekers could easily search and apply for jobs online. The introduction of AOL's Instant Messaging feature provided an even faster means for employers and candidates to communicate and schedule interviews. As smartphones became more pervasive in the early 2000s, hiring managers increasingly used phone calls for screening and interviewing candidates. Despite this trend, over 80% of interviews still took place in person.
A Potential TikTok Ban?!
As you may already know, there has been a lot of talk lately about the possibility of a TikTok ban. While this has not yet come to fruition, it's important to consider the implications this could have for businesses and recruiters who rely on TikTok as a platform to market their brand, recruit new talent, and connect with their audience.
The Effects of Workplace Racism and Sexism
One day it's a covert statement to a mother returning to work after maternity leave. Another day it's a lingering gaze at an employee enjoying a culturally rich meal. These microaggressions (or sometimes macroaggressions) can take an employee from a confident, high-performer to one that feels insecure being themselves at work. Your employees engage with people with different ideas and feel most comfortable and valued when they can work without losing their cultural, racial, and gender identity. While most employers know this, why have workplace racism and sexism often been neglected?
When Rage Applying Strikes: How to Identify Unserious Candidates
As the job market remains highly competitive, we have seen a surge in "rage applying." This is when candidates apply to multiple jobs, often without considering whether they are truly interested in the role. Rage applying goes hand-in-hand with quiet quitting. Often, employees want to entertain the thoughts and feelings of leaving their job, but they aren't necessarily serious about leaving yet. Meanwhile, other employees engaging in this trend are actually trying to find a better role. As a recruiter, it can be hard to identify who are the real applicants in a sea full of quiet quitters, but understanding rage applying and identifying red flags will certainly help.
How to Increase Job Ad Exposure
In today's competitive job market, writing quality job ads is critical for attracting top talent to your organization. While networking and candidate referrals are prime real estate for finding qualified candidates, nothing beats the tried-and-true method of writing an extraordinary job ad. But while writing a great job ad is the first step, what's more important is increasing visibility. You could have the most detailed, well-written ad on the internet, but if no one sees it, then you are wasting time (and potentially money!). Employers often believe that job boards are the root of the problem, but you can learn how to increase job ad exposure by tweaking a few steps of your recruitment process.
How to Navigate Hiring Out of State
The job market has shifted significantly in recent years. The accelerated adoption of technology has not only pushed many companies into remote working arrangements but also increased the availability of supporting tools and technologies (i.e., video conferencing and collaboration software).