​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.

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).

• Programming Languages: Python, Java, or other applicable programming languages
• ML Frameworks: TensorFlow, PyTorch, Scikit-learn.
• CI/CD Tools: GitHub Actions, Jenkins, GitLab CI/CD
• Containerization: Docker, Kubernetes
• Cloud Platforms: Snowflake AI Data Cloud, GCPData Processing: Java, Python, SQL (accessing data in Snowflake and GCP BigQuery)
• Version Control: GitHub and/or BitBucket
• Excellent communication skills, both written and verbal.Build relationships

• Develop people
• Lead change
• Inspire Others
• Think critically
• Communicate clearly
• Create Accountability

Benefits Overview:

Benefits are subject to change and may be subject to specific elections, plan, or program terms.  This role is eligible for the following:

• Medical, dental & vision
• Hospital plans
• 401(k) Retirement Plan – Pre-tax and Roth post-tax contributions available
• Life Insurance (Company paid Basic Life and AD&D as well as voluntary Life & AD&D for the employee and dependents)
• Company paid Short and long-term disability
• Health & Dependent Care Spending Accounts (HSA & DCFSA)
• Transportation benefits
• Employee Assistance Program
• Tuition Assistance
• Time Off/Leave (PTO, Allegis Group Paid Family Leave, Parental Leave)

• This position is bonus eligible. 
• 59,100-88,700