Data Engineer with C++ (hybrid)
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Data Engineer with C++ in Washington, DC, offering a 3-6 month contract at $65-75/hr. Key skills include proficiency in Python, R, SQL, C++, machine learning, and cloud platforms.
🌎 - Country
United States
💱 - Currency
$ USD
💰 - Day rate
Unknown
Unknown
600
🗓️ - Date discovered
May 20, 2025
🕒 - Project duration
3 to 6 months
🏝️ - Location type
Hybrid
📄 - Contract type
W2 Contractor
🔒 - Security clearance
Unknown
📍 - Location detailed
Washington, DC 20005
🧠 - Skills detailed
#Calculus #Matplotlib #Data Wrangling #ML (Machine Learning) #AI (Artificial Intelligence) #Regression #Reinforcement Learning #Tableau #SQL (Structured Query Language) #TensorFlow #Azure #Data Manipulation #Programming #Mathematics #Data Engineering #Cloud #C++ #Java #Visualization #Data Science #Big Data #AWS (Amazon Web Services) #Python #Database Systems #Deep Learning #NLP (Natural Language Processing) #PyTorch #Sentiment Analysis #Data Processing #Database Management #Scala #Spark (Apache Spark) #"ETL (Extract #Transform #Load)" #Hadoop #NoSQL #R
Role description
Data Engineer with C++ Washington, DC - hybrid 3-6 month contract $65-75/hr W2 Technical Skills: Programming:
Proficiency in Python and R is crucial. These languages are the workhorses of data science.
Strong SQL skills for database management and data retrieval.
C++ knowledge/experience
Familiarity with other languages like Scala or Java for big data processing can be beneficial.
Statistical Analysis and Mathematics:
A solid understanding of statistical concepts like probability, hypothesis testing, and regression analysis.
Knowledge of linear algebra, calculus, and other mathematical foundations.
Ability to apply statistical methods to extract meaningful insights from data.
Machine Learning and Artificial Intelligence (AI):
Expertise in various machine learning algorithms (e.g., supervised, unsupervised, reinforcement learning).
Deep learning knowledge for complex tasks like image and natural language processing.
Experience with machine learning frameworks like scikit-learn, TensorFlow, and PyTorch.
Data Wrangling and Database Management:
Ability to clean, preprocess, and transform data from various sources.
Experience with database systems (e.g., relational, NoSQL).
Proficiency in data manipulation tools and techniques.
Data Visualization:
Ability to create clear and compelling visualizations using tools like Matplotlib, Seaborn, and Tableau.
Skill in communicating data insights effectively through visual representations.
Big Data Technologies:
Familiarity with big data platforms like Hadoop and Spark. (optional)
(essential)Knowledge of cloud computing platforms (e.g., AWS, Azure, Google Cloud).
Natural Language Processing (NLP):
Understanding of NLP techniques for text analysis, sentiment analysis, and language modeling.
#M2 Ref: #850-Rockville (ALTA IT)
Data Engineer with C++ Washington, DC - hybrid 3-6 month contract $65-75/hr W2 Technical Skills: Programming:
Proficiency in Python and R is crucial. These languages are the workhorses of data science.
Strong SQL skills for database management and data retrieval.
C++ knowledge/experience
Familiarity with other languages like Scala or Java for big data processing can be beneficial.
Statistical Analysis and Mathematics:
A solid understanding of statistical concepts like probability, hypothesis testing, and regression analysis.
Knowledge of linear algebra, calculus, and other mathematical foundations.
Ability to apply statistical methods to extract meaningful insights from data.
Machine Learning and Artificial Intelligence (AI):
Expertise in various machine learning algorithms (e.g., supervised, unsupervised, reinforcement learning).
Deep learning knowledge for complex tasks like image and natural language processing.
Experience with machine learning frameworks like scikit-learn, TensorFlow, and PyTorch.
Data Wrangling and Database Management:
Ability to clean, preprocess, and transform data from various sources.
Experience with database systems (e.g., relational, NoSQL).
Proficiency in data manipulation tools and techniques.
Data Visualization:
Ability to create clear and compelling visualizations using tools like Matplotlib, Seaborn, and Tableau.
Skill in communicating data insights effectively through visual representations.
Big Data Technologies:
Familiarity with big data platforms like Hadoop and Spark. (optional)
(essential)Knowledge of cloud computing platforms (e.g., AWS, Azure, Google Cloud).
Natural Language Processing (NLP):
Understanding of NLP techniques for text analysis, sentiment analysis, and language modeling.
#M2 Ref: #850-Rockville (ALTA IT)
