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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 · 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 ...

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 ...

Data Engineer

Washington, DC · On-site

$80K - $120K/yr

Bachelor's degree in Data Engineering, Computer Science, Software Engineering, or related field. * AWS Data Engineer Associate, AWS Certified Data Analytics, Azure Data Engineer Associate, or ...

Data Engineer

Washington, DC · On-site

$80K - $120K/yr

Bachelor's degree in Data Engineering, Computer Science, Software Engineering, or related field. * AWS Data Engineer Associate, AWS Certified Data Analytics, Azure Data Engineer Associate, or ...

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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:

$68K - $68K/yr

Full-time

Re-posted 4 days ago


Job description

Job Summary:
Carnegie Mellon University's Software Engineering Institute is seeking an Associate Data Scientist to leverage advanced statistics and machine learning in addressing cybersecurity challenges for government and industry clients. The role involves collaborating with elite professionals to develop prototype solutions, conduct research, and present findings at conferences.
Responsibilities:
• Identify areas where advanced statistical techniques can help tackle problems.
• Plan and develop prototype solutions.
• Build out final products.
• Co-author research proposals.
• Execute studies and present findings to DoW sponsors and at academic conferences.
Qualifications:
Required:
• BS in data science, machine learning, computer science, statistics, or related highly-quantitative discipline with three (3) years of experience or equivalent combination of training or experience; or MS in data science, machine learning, computer science, statistics, or related highly-quantitative discipline with one (1) year of experience; or PhD in data science, machine learning, computer science, statistics, or related highly-quantitative discipline.
• Willingness to complete modest travel to various locations to support the SEI’s overall mission.
• You will be subject to a background check and must be able obtain and maintain a U.S. Department of War security clearance.
• Experience in predictive modeling, data science, and/or AI & machine learning
• Deep understanding of statistical modeling techniques and advanced data analytics
• Proficient with at least one mathematical/statistical programming package (e.g., R, python numpy/scipy/pandas/polars, MATLAB, etc.)
• Innovative and inquisitive with ability to imagine novel analytical solutions to problems Thrives in a multi-disciplinary environment
• Strong communication skills
• Expertise in one or more of the following: Recommendation systems, Time-series forecasting (Prophet, NeuralProphet, Chronos, Lag-Llama, etc.), NLP / LLMs (fine-tuning, RAG, evaluation, prompt engineering), Causal inference / uplift modeling / synthetic controls, Modern ML frameworks: LightGBM/XGBoost, CatBoost, PyTorch,JAX, TensorFlow), LLMs / agentic workflows (LangChain/LlamaIndex/Haystack), Experience deploying models (FastAPI, Triton, KServe, SageMaker, Vertex AI, or similar), Experience working with big data (Spark, Trino, Snowflake, BigQuery, Databricks)
Preferred:
• Experience in cybersecurity and privacy is a plus
• Experience in U.S. Government work and/or with FFRDCs, UARCs an National Labs is a plus
• Demonstrated ability to learn new concepts and grow into new areas of work
Company:
We conduct cutting-edge research and development that accelerates the transition of technology to the Department of War (DoW), delivering measurable impact in support of the national security mission. Founded in 1984, the company is headquartered in Pittsburgh, USA, with a team of 501-1000 employees. The company is currently Late Stage.