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Associate Data Engineer information
See Columbia, MD salary details
$9.70 - $11.57
6% of jobs
$11.57 - $13.44
3% of jobs
$15.17 is the 25th percentile. Wages below this are outliers.
$13.44 - $15.32
17% of jobs
The median wage is $16.88 / hr.
$15.32 - $17.19
28% of jobs
$18.99 is the 75th percentile. Wages above this are outliers.
$17.19 - $19.06
21% of jobs
$19.06 - $20.93
8% of jobs
$20.93 - $22.80
7% of jobs
$22.80 - $24.67
5% of jobs
$24.67 - $26.54
2% of jobs
$26.54 - $28.42
1% of jobs
$28.42 - $30.29
0% of jobs
$9
$18
$30
How much do associate data engineer jobs pay per hour?
What are the key skills and qualifications needed to thrive as an associate data engineer?
What is the difference between Associate Data Engineer vs Data Engineer?
| Aspect | Associate Data Engineer | Data Engineer |
|---|---|---|
| Required Credentials | Bachelor's degree in CS, Data Science, or related field; basic knowledge of SQL and Python | Bachelor's or Master's degree; advanced knowledge of SQL, Python, Spark, and cloud platforms |
| Work Environment | Entry-level, team-focused, often in tech or finance industries | Mid to senior level, designing and maintaining data pipelines in various industries |
| Employer & Industry Usage | Common in tech companies, startups, and finance firms | Used across industries for building scalable data infrastructure |
| Common Search & Comparison | Often compared for career progression and skill requirements |
The Associate Data Engineer role is an entry-level position focusing on supporting data infrastructure, while the Data Engineer is a more advanced role responsible for designing and maintaining complex data systems. The roles share similar educational backgrounds and work environments but differ in experience level and responsibilities.
What does an associate data engineer do?
What are some common challenges an associate data engineer may face when working with large-scale data pipelines?
Senior Associate, Data Scientist - Commercial Bank Strategy & Analytics
Mclean, VA • On-site
Full-time
Posted 18 days ago
Capital One rating
7.7
Based on 146 frontline employees who took The Breakroom Quiz
93rd of 170 rated banks
Job description
Data is at the center of everything we do. As a startup, we disrupted the credit card industry by individually personalizing every credit card offer using statistical modeling and the relational database, cutting edge technology in 1988! Fast-forward a few years, and this little innovation and our passion for data has skyrocketed us to a Fortune 200 company and a leader in the world of data-driven decision-making.
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.
Team Description
Capital One's Commercial Bank Team has a $100B+ loan portfolio that has grown both organically and via acquisitions, covering Corporate & Industrial, Commercial Real Estate, and Structured Finance Products. On this team, you'll get an opportunity to solve a diverse set of problems, with a diverse set of tools. In some settings, you'll leverage open source programming or cloud computing to predict outcomes across multi-million record datasets. In other settings, you'll get the opportunity to use completely different skill sets, blending business thinking with quantitative tools when forecasting rare or unprecedented events. It's a growing team, full of exciting opportunities to solve a range of complex problems.
Role Description
In this role, you will:
- Partner with a cross-functional team of data scientists, software engineers, and product managers to deliver a product customers love
- Leverage a broad stack of technologies - Python, Conda, AWS, H2O, Spark, and more - to reveal the insights hidden within huge volumes of numeric and textual data
- Build machine learning models through all phases of development, from design through training, evaluation, validation, and implementation
- Flex your interpersonal skills to translate the complexity of your work into tangible business goals
The Ideal Candidate is:
- Innovative. You continually research and evaluate emerging technologies. You stay current on published state-of-the-art methods, technologies, and applications and seek out opportunities to apply them.
- Creative. You thrive on bringing definition to big, undefined problems. You love asking questions and pushing hard to find answers. You're not afraid to share a new idea.
- Technical. You're comfortable with open-source languages and are passionate about developing further. You have hands-on experience developing data science solutions using open-source tools and cloud computing platforms.
- Statistically-minded. You've built models, validated them, and backtested them. You know how to interpret a confusion matrix or a ROC curve. You have experience with clustering, classification, sentiment analysis, time series, and deep learning.
- A data guru. "Big data" doesn't faze you. You have the skills to retrieve, combine, and analyze data from a variety of sources and structures. You know understanding the data is often the key to great data science.
Basic Qualifications:
- Currently has, or is in the process of obtaining one of the following with an expectation that the required degree will be obtained on or before the scheduled start date:
- A Bachelor's Degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) plus 2 years of experience performing data analytics
- A Master's Degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) or an MBA with a quantitative concentration
Preferred Qualifications:
- Master's Degree in "STEM" field (Science, Technology, Engineering, or Mathematics), or PhD in "STEM" field (Science, Technology, Engineering, or Mathematics)
- Experience working with AWS
- At least 2 years' experience in Python
- At least 2 years' experience with machine learning
- At least 2 years' experience with SQL
Capital One will consider sponsoring a new qualified applicant for employment authorization for this position.
The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked.
McLean, VA: $135,600 - $154,800 for Sr Assoc, Data Science
New York, NY: $148,000 - $168,900 for Sr Assoc, Data Science
Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter.
This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan.
Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level.
This role is expected to accept applications for a minimum of 5 business days.
No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries.
If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations.
For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com
Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site.
Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
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