Data Engineer
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Senior Data Engineer in Stevenage, UK, for a 6+ month contract, with a pay rate of "unknown." Key skills include 5+ years in data science, proficiency in Python/R, and experience with ML and GenAI in production.
🌎 - Country
United Kingdom
💱 - Currency
£ GBP
-
💰 - Day rate
-
🗓️ - Date discovered
September 13, 2025
🕒 - Project duration
More than 6 months
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🏝️ - Location type
On-site
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📄 - Contract type
Unknown
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🔒 - Security clearance
Unknown
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📍 - Location detailed
Stevenage, England, United Kingdom
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🧠 - Skills detailed
#Cloud #R #Azure #Data Wrangling #SageMaker #Lambda (AWS Lambda) #NumPy #Quality Assurance #Datasets #Libraries #Scala #Computer Science #Data Engineering #Deep Learning #Pandas #PyTorch #Deployment #Data Exploration #Hugging Face #Spark (Apache Spark) #Python #TensorFlow #Programming #Model Deployment #GCP (Google Cloud Platform) #Time Series #AWS (Amazon Web Services) #Hadoop #Documentation #Langchain #Forecasting #Transformers #"ETL (Extract #Transform #Load)" #ML (Machine Learning) #AI (Artificial Intelligence) #Data Science #Big Data
Role description
Senior Data Engineer
Stevenage, UK
6 Months+ (long term project)
KEY RESPONSIBILITIES:
In this role, you will be responsible for:
• Conduct extensive data exploration, pre-processing, and quality assurance.
• Design and implement data science methodologies for structured and unstructured datasets.
• Apply predictive analytics, time series forecasting, and statistical modeling.
• Engineer features and optimize model performance.
• Train, evaluate, and deploy ML models using classical and deep learning techniques.
• Integrate and operationalize LLMs and Generative AI models using frameworks like LangChain, Hugging Face, and OpenAI.
• Leverage AWS services such as Bedrock, SageMaker, and Lambda for scalable model deployment.
• Implement Retrieval-Augmented Generation (RAG) pipelines and prompt engineering strategies.
• Monitor model performance, detect drift, and manage retraining workflows.
• Collaborate with cross-functional teams to embed AI capabilities into business applications.
• Stay abreast of advancements in AI, GenAI, and cloud technologies.
• Mentor junior engineers and contribute to knowledge sharing.
• Maintain comprehensive documentation of data workflows and model lifecycles.
• Experience and understanding of Agentic AI and MCP servers.
Key Performance Indicators (KPIs) for the role:
Over the next 12 months, this role’s success will be measured on:
• Successful deployment of data science models into production.
• Improvement in model performance metrics (e.g., accuracy, precision, recall).
• Effective data-driven decision-making supported by predictive analytics and statistical models.
• Timely identification and mitigation of model drift.
• Effective collaboration with cross-functional teams.
• Mentorship and development of junior team members.
• Successful deployment of GenAI and ML models into production.
• Effective use of LLMs and foundational models in business applications.
KEY JOB REQUIREMENTS:
In this role, you will be successful if you have:
Experience:
• 5+ years of experience in data science.
• Strong understanding of data science techniques, including statistical modelling and data analytics.
• Experience with data science libraries (e.g., NumPy, pandas, scikit-learn).
• Proven experience with ML, GenAI, and LLMs in production environments.
Skills & Competencies:
Must Have:
• Proficiency in Python, R, or other relevant programming languages.
• Proficiency in working with large datasets, data wrangling, and data pre-processing.
• Hands-on with ML libraries (e.g., scikit-learn, XGBoost, TensorFlow, PyTorch).
• Ability to work independently and lead projects from inception to deployment.
• Experience with big data technologies (e.g., Hadoop, Spark) and cloud platforms (e.g., AWS, GCP, Azure).
• Familiarity with LLMs, prompt engineering, pre-training, and fine-tuning techniques.
• Experience with AWS Bedrock, SageMaker, and GenAI pipelines.
Preferred Skills:
• MSc or PhD in Data Science, Computer Science, or related field.
• Experience with LangChain, RAG, Vector DBs (e.g., FAISS, Pinecone), and Hugging Face Transformers.
ADDITIONAL NOTES:
• Ability to work independently or as part of a team.
• Strong communication and stakeholder management skills.
• Passion for innovation and continuous learning in AI.
Please reach @ Richa.c@responseinformatics.com
Senior Data Engineer
Stevenage, UK
6 Months+ (long term project)
KEY RESPONSIBILITIES:
In this role, you will be responsible for:
• Conduct extensive data exploration, pre-processing, and quality assurance.
• Design and implement data science methodologies for structured and unstructured datasets.
• Apply predictive analytics, time series forecasting, and statistical modeling.
• Engineer features and optimize model performance.
• Train, evaluate, and deploy ML models using classical and deep learning techniques.
• Integrate and operationalize LLMs and Generative AI models using frameworks like LangChain, Hugging Face, and OpenAI.
• Leverage AWS services such as Bedrock, SageMaker, and Lambda for scalable model deployment.
• Implement Retrieval-Augmented Generation (RAG) pipelines and prompt engineering strategies.
• Monitor model performance, detect drift, and manage retraining workflows.
• Collaborate with cross-functional teams to embed AI capabilities into business applications.
• Stay abreast of advancements in AI, GenAI, and cloud technologies.
• Mentor junior engineers and contribute to knowledge sharing.
• Maintain comprehensive documentation of data workflows and model lifecycles.
• Experience and understanding of Agentic AI and MCP servers.
Key Performance Indicators (KPIs) for the role:
Over the next 12 months, this role’s success will be measured on:
• Successful deployment of data science models into production.
• Improvement in model performance metrics (e.g., accuracy, precision, recall).
• Effective data-driven decision-making supported by predictive analytics and statistical models.
• Timely identification and mitigation of model drift.
• Effective collaboration with cross-functional teams.
• Mentorship and development of junior team members.
• Successful deployment of GenAI and ML models into production.
• Effective use of LLMs and foundational models in business applications.
KEY JOB REQUIREMENTS:
In this role, you will be successful if you have:
Experience:
• 5+ years of experience in data science.
• Strong understanding of data science techniques, including statistical modelling and data analytics.
• Experience with data science libraries (e.g., NumPy, pandas, scikit-learn).
• Proven experience with ML, GenAI, and LLMs in production environments.
Skills & Competencies:
Must Have:
• Proficiency in Python, R, or other relevant programming languages.
• Proficiency in working with large datasets, data wrangling, and data pre-processing.
• Hands-on with ML libraries (e.g., scikit-learn, XGBoost, TensorFlow, PyTorch).
• Ability to work independently and lead projects from inception to deployment.
• Experience with big data technologies (e.g., Hadoop, Spark) and cloud platforms (e.g., AWS, GCP, Azure).
• Familiarity with LLMs, prompt engineering, pre-training, and fine-tuning techniques.
• Experience with AWS Bedrock, SageMaker, and GenAI pipelines.
Preferred Skills:
• MSc or PhD in Data Science, Computer Science, or related field.
• Experience with LangChain, RAG, Vector DBs (e.g., FAISS, Pinecone), and Hugging Face Transformers.
ADDITIONAL NOTES:
• Ability to work independently or as part of a team.
• Strong communication and stakeholder management skills.
• Passion for innovation and continuous learning in AI.
Please reach @ Richa.c@responseinformatics.com
