Data Engineer

​In Office Requirements:


* Required in-office presence at least 4 days per week.

Job Summary:

Data Engineer - In this role, the engineer will be responsible for Acquire and integrate new data sources into the larger Enterprise Data program at Allegis Group.

Implementing, and maintaining robust machine learning pipelines that support our data-driven initiatives.

Data Engineer will work closely with data scientists, software engineers, and IT operations to ensure seamless integration and deployment of machine learning models into production environments.

ML-Ops pipelines will include automating the end-to-end ML lifecycle, optimizing model performance, and ensuring compliance with data governance and security policies.

Responsibilities

Essential Functions:


* Design and develop scalable machine learning pipelines to automate the end-to-end ML lifecycle


* Collaborate with data scientists to understand model requirements and translate them into efficient pipeline architectures.


* Implement CI/CD practices for ML models, ensuring reliable and repeatable deployment processes.


* Monitor and optimize the performance of ML models in production, addressing issues related to scalability, latency, and collaborate with data scientists on accuracy of model in production.


* Maintain and improve the infrastructure for data collection, storage, and processing, utilizing the Snowflake Cloud Data Platform.


* Ensure compliance with data governance and security policies.


* Provide support and troubleshooting for ML pipeline-related issues.Bachelor's or master's degree in computer science, Engineering, or a related field.


* 2+ years' experience in designing and implementing machine learning pipelines.


* 2+ years programming skills in languages such as Python, Java, or other applicable programming languages.


* 2+ years' experience with the Snowflake AI Data Cloud and SQL based database technologies (Oracle, mySQL, PostgreSQL).


* Strong problem-solving skills and the ability to work collaboratively in a team environment.


* Experience with ML frameworks and libraries (e.g., TensorFlow, Scikit-learn, or equivalent machine and deep learning libraries.).


* Experience with experience natural language processing models, using NLP toolkits such as NLTK, OpenNLP, Stanford CoreNLP etc.


* Experience with statistical analysis with an understanding of a variety of ML algorithms.


* Knowledge of cloud platforms (e.g., GCP, Snowflake) and their ML services.


* Familiarity with Agile processes and practices.


* Familiarity or ability to quickly learn data engineering GUI tools like Matillion


* Familiarity with CI/CD tools (e.g., Jenkins, GitLab CI/CD) and containerization technologies (e.g., Docker, Kubernetes).

Qualifications

Skills/Abilities:



* Programming Languages: Python, Java, or other applicable programming languages


* ML Frameworks: TensorFlow, PyTorch, Scikit-lea...