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Associate Data Engineering Jobs in Washington (NOW HIRING)

Associate Data Scientist

Washington, DC · On-site

$66K - $67K/yr

You are passionate about maintaining the high scientific and engineering standards required to ... Associate Data Scientist position on our Data Science team. The Data Science team works closely ...

Associate Data Scientist

Washington, DC

$66K - $67K/yr

You are passionate about maintaining the high scientific and engineering standards required to ... Associate Data Scientist position on our Data Science team. The Data Science team works closely ...

Principal Associate, Data Scientist

Mclean, VA · On-site

$59K - $60K/yr

Principal Associate, Data Scientist Data is at the center of everything we do. As a startup, we ... Master's Degree in "STEM" field (Science, Technology, Engineering, or Mathematics) plus 3 years of ...

As a Senior Data Center Technician, you will act as a point of escalation for L1 associate data center engineers and L2 data center engineers. This position will work directly with our contracted L2 ...

Principal Associate, Data Scientist Data is at the center of everything we do. As a startup, we ... Master's Degree in "STEM" field (Science, Technology, Engineering, or Mathematics) plus 3 years of ...

Associate Data Scientist

Arlington, VA · On-site

$67K - $68K/yr

Data Scientists at the SEI use advanced statistics, data analytics, machine learning, and ... Proficient with at least one mathematical/statistical programming package (e.g., R, python numpy ...

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Associate Data Engineering information

What are some typical projects an Associate Data Engineer might work on in their first year?

In their first year, an Associate Data Engineer often works on building and maintaining data pipelines, cleaning and transforming raw data, and supporting the integration of new data sources. They may also assist in optimizing existing data workflows for better performance and reliability, as well as collaborating closely with data analysts and senior engineers to ensure data quality and accessibility. These projects help new team members develop a strong understanding of the organization's data infrastructure and best practices in data engineering.

What does an associate data engineer do?

An associate data engineer supports data collection, processing, and storage by developing and maintaining data pipelines and workflows. They often work with tools like SQL, Python, and cloud platforms, and may assist in data quality and integration tasks under the supervision of senior engineers.

What are the key skills and qualifications needed to thrive as an Associate Data Engineer, and why are they important?

To thrive as an Associate Data Engineer, a solid understanding of database systems, SQL, data modeling, and a relevant bachelor's degree in computer science or a related field is essential. Familiarity with ETL tools, cloud platforms like AWS or Azure, and programming languages such as Python or Java is typically required. Strong problem-solving abilities, attention to detail, and effective communication skills help set candidates apart in collaborative, data-driven environments. These skills and qualities are crucial for building reliable data pipelines, ensuring data quality, and enabling actionable business insights.

What is an Associate Data Engineer?

An Associate Data Engineer is an entry-level professional who assists in designing, building, and maintaining data pipelines and infrastructure. They typically work with senior data engineers to ensure data is collected, stored, and processed efficiently for analytics and business use. Responsibilities often include data cleaning, integration, and supporting the development of scalable data solutions. Associate Data Engineers usually have foundational knowledge of programming, databases, and cloud technologies.

What engineers make $500,000?

Senior data engineers, especially those with extensive experience, advanced skills in cloud platforms, and expertise in big data tools, can earn $500,000 or more annually. High compensation often involves leadership roles, specialized knowledge, or working in high-demand industries such as finance or technology. Achieving this level typically requires a combination of technical proficiency, certifications, and strategic career development.

What is the difference between Associate Data Engineering vs Data Engineer?

AspectAssociate Data EngineeringData Engineer
Required CredentialsBachelor's degree in CS, IT, or related field; some certificationsBachelor's or master's degree; extensive experience preferred
Work EnvironmentEntry-level, team-focused, supporting data pipelinesDesigning, building, and maintaining large-scale data systems
Employer & Industry UsageCommon in tech companies, finance, healthcareUsed across industries for advanced data infrastructure roles
Search & Comparison IntentEntry-level, learning, support rolesAdvanced, specialized data infrastructure roles

The main difference between Associate Data Engineering and Data Engineer lies in experience and responsibilities. Associate Data Engineers are typically entry-level, focusing on supporting data pipelines and gaining hands-on experience. Data Engineers have more experience, handling complex data architecture, optimization, and system design. Both roles require similar educational backgrounds, but Data Engineers usually have more technical expertise and responsibility.

Can I make 200K as a data engineer?

Senior data engineers with extensive experience, specialized skills in tools like Spark or cloud platforms, and working in high-cost-of-living areas can earn salaries around or above $200,000 annually. Entry-level or mid-level data engineers typically earn less, with salaries increasing with expertise, certifications, and industry demand.

What engineers make 200,000 a year?

Senior data engineers and specialized software engineers often earn $200,000 or more annually, especially with extensive experience, advanced skills in cloud platforms, and certifications. High salaries are common in competitive markets and large organizations that require complex data infrastructure and engineering expertise.
What are the most commonly searched types of Data Engineering jobs in Washington? The most popular types of Data Engineering jobs in Washington are:
Principal Associate, Data Scientist - Card DFS Integration

Principal Associate, Data Scientist - Card DFS Integration

Capital One

Mclean, VA • On-site

$59K - $60K/yr

Full-time

Re-posted 23 days ago


Capital One rating

7.8

Company rating: 7.8 out of 10

Based on 143 frontline employees who took The Breakroom Quiz

72nd of 146 rated banks


Job description

Principal Associate, Data Scientist - Card DFS Integration

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

The Discover Card Customer Management Data Science team is responsible for ensuring all models used to underwrite the Discover Card portfolio are well-managed and creating the destination state that builds on the best of both worlds from both Discover's models and Capital One's models.

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

The Ideal Candidate is:

  • Customer first. You love the process of analyzing and creating, but also share our passion to do the right thing. You know at the end of the day it's about making the right decision for our customers.

  • 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.

  • 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 5 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 plus 3 years of experience performing data analytics

    • A PhD in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field)

Preferred Qualifications:

  • Master's Degree in "STEM" field (Science, Technology, Engineering, or Mathematics) plus 3 years of experience in data analytics, or PhD in "STEM" field (Science, Technology, Engineering, or Mathematics)

  • At least 1 year of experience working with AWS

  • At least 3 years of experience in Python, Scala, or R

  • At least 3 years of experience with machine learning

  • At least 3 years of 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.

Chicago, IL: $147,100 - $167,900 for Princ Associate, Data Science


McLean, VA: $161,800 - $184,600 for Princ Associate, Data Science


Riverwoods, IL: $147,100 - $167,900 for Princ Associate, 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 theCapital 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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