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Mlops Data Engineer Jobs in Connecticut (NOW HIRING)

Data Engineer

Newington, CT

$114K - $136K/yr

In alignment with current industrys best practices, this role integrates advanced data engineering, software development, and machine learning operations (MLOps) to deliver secure, scalable, and high ...

Data Engineer

Newington, CT · On-site

$114K - $137K/yr

In alignment with current industry?s best practices, this role integrates advanced data engineering, software development, and machine learning operations (MLOps) to deliver secure, scalable, and ...

Data Engineer

Newington, CT · On-site

$114K - $136K/yr

In alignment with current industry's best practices, this role integrates advanced data engineering, software development, and machine learning operations (MLOps) to deliver secure, scalable, and ...

Data Engineer

Hartford, CT · Hybrid

$100K - $151K/yr

We use the latest data technologies, software engineering practices, MLOPs, Agile delivery frameworks, and are passionate about building well-architected and innovative solutions that drive business ...

ClifyX is seeking an MLOps Engineer to enhance their machine learning operations. The primary ... and scale reliable data pipelines using AWS (Python, PySpark and Snowflake) • Bash/Shell ...

ClifyX is seeking a GEN AI Data Scientist Engineer with over 8 years of experience. The role ... MLOps, DevOps, and Deployment • Agile, customer communication and offshore coordination and ...

... and HR data domains. * 2+ years of experience operationalizing LLMOps/MLOps capabilities ... We are hiring an AI Engineer to build and operate the data, features, and GenAI foundations that ...

... and HR data domains. * 2+ years of experience operationalizing LLMOps/MLOps capabilities ... We are hiring an AI Engineer to build and operate the data, features, and GenAI foundations that ...

Senior AI Machine Learning Engineer

Hartford, CT · Hybrid

$123K - $162K/yr

The Hartford seeks a driven, team-focused Senior AI Machine Learning Engineer to build Machine Learning Operations (MLOps) services for the Customer Operations Data Science team. The Hartford is ...

Data engineering experience with Spark, Airflow/dbt, streaming, data modeling or ML/data science background feature engineering, experimentation or model evaluation * Experience with MLOps/LLMOps ...

Data engineering experience with Spark, Airflow/dbt, streaming, data modeling or ML/data science background feature engineering, experimentation or model evaluation * Experience with MLOps/LLMOps ...

Data engineering experience with Spark, Airflow/dbt, streaming, data modeling or ML/data science background feature engineering, experimentation or model evaluation * Experience with MLOps/LLMOps ...

Data engineering experience with Spark, Airflow/dbt, streaming, data modeling or ML/data science background feature engineering, experimentation or model evaluation * Experience with MLOps/LLMOps ...

Sr Data Engineer - GE07BE We're determined to make a difference and are proud to be an insurance ... Adopt and promote MLOps best practices to the Data Science community. Minimum Requirements * Must ...

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Mlops Data Engineer information

What is an MLOps data engineer?

MLOps Data Engineers are professionals who blend expertise in machine learning (ML), operations (Ops), and data engineering to streamline the deployment and management of ML models in production environments. They design and maintain data pipelines, automate workflows, and ensure the scalability, reliability, and reproducibility of machine learning systems. Their role bridges the gap between data scientists and IT operations, enabling seamless integration of ML models into real-world applications.

What are the key skills and qualifications needed to thrive as an MLOps data engineer?

To thrive as an MLOps Data Engineer, you need a strong background in data engineering, machine learning workflows, and software development, usually supported by a degree in computer science or a related field. Expertise with cloud platforms (such as AWS, GCP, or Azure), CI/CD pipelines, containerization tools (like Docker and Kubernetes), and familiarity with orchestration frameworks are typically required, along with certifications in cloud or data engineering. Strong problem-solving abilities, collaboration, and clear communication set professionals apart in this role. These skills and qualities are critical to efficiently deploying scalable machine learning solutions and ensuring smooth collaboration between data science and engineering teams.

What are some common challenges MLOps data engineers face when deploying machine learning models into production?

MLOps Data Engineers often encounter challenges such as ensuring seamless integration between data pipelines and model serving infrastructure, managing consistent data quality, and automating model retraining and monitoring. Another common hurdle is maintaining scalability and reliability as data volumes grow, and efficiently collaborating with data scientists, software engineers, and DevOps teams. Addressing these challenges requires strong communication skills, familiarity with cloud platforms, and a proactive approach to troubleshooting and automation.

What is the difference between Mlops Data Engineer vs Data Scientist?

AspectMlops Data EngineerData Scientist
Required SkillsMachine learning deployment, cloud platforms, scripting, data pipelinesStatistical analysis, programming, data visualization, machine learning modeling
CertificationsCloud certifications, ML engineering coursesData science certifications, statistical courses
Work EnvironmentData pipelines, cloud infrastructure, ML deployment systemsData analysis, modeling, research environments
Industry UsageTech companies, AI-focused firms, cloud service providersResearch institutions, analytics firms, tech companies

The main difference between an Mlops Data Engineer and a Data Scientist lies in their focus areas. Mlops Data Engineers specialize in deploying, maintaining, and scaling machine learning models within production environments, emphasizing infrastructure and automation. Data Scientists primarily focus on analyzing data, building models, and deriving insights. Both roles require strong technical skills, but their day-to-day tasks and career paths differ significantly.

Are MLOps Data Engineers in demand?

MLOps Data Engineers are in high demand due to the increasing adoption of machine learning and AI across industries. They are skilled in deploying, managing, and maintaining ML models using tools like Docker, Kubernetes, and cloud platforms, making their expertise highly sought after in data-driven organizations.

Is MLOps required for data engineers?

MLOps is increasingly important for data engineers involved in deploying and maintaining machine learning models, as it encompasses practices like automation, monitoring, and version control. While not always mandatory, knowledge of MLOps tools such as Docker, Kubernetes, and CI/CD pipelines enhances a data engineer's ability to support scalable and reliable ML systems.

What are popular job titles related to Mlops Data Engineer jobs in Connecticut?

For Mlops Data Engineer jobs in Connecticut, the most frequently searched job titles are:

What cities in Connecticut are hiring for Mlops Data Engineer jobs?

Cities in Connecticut with the most Mlops Data Engineer job openings:

$114K - $136K/yr

Full-time

Re-posted 21 days ago


Job description

OVERVIEW OF POSITION: The Data Engineer is a strategic technical role responsible for architecting, building, and sustaining the organizations modern data ecosystem, including cloud-based data platforms, analytics environments, and AI/ML capabilities. In alignment with current industrys best practices, this role integrates advanced data engineering, software development, and machine learning operations (MLOps) to deliver secure, scalable, and high-performance solutions across the enterprise.This position designs and manages end-to-end data pipelines, develops cloud-native and on-premise data architectures, and transforms raw structured and unstructured data into high-quality, trusted information assets that support decision-making and mission-critical operations. The Data Engineer also builds custom applications, automation tools, and reusable data services to streamline workflows and accelerate digital transformation efforts.In addition, this role leads the operationalization of machine learning models, ensuring they are reproducible, observable, and deployed with robust CI/CD and MLOps practices to solve complex business and operational challenges.Operating within the aerospace and defense sector, the Data Engineer collaborates closely with cross-functional teams to maximize data value, enhance data quality, and maintain strict compliance with Cybersecurity Maturity Model Certification (CMMC) requirements and the National Institute of Standards and Technology (NIST) Special Publication 800-171 security controls

This position does not require security clearance. ESSENTIAL JOB FUNCTIONS: Data Architecture and Business Intelligence Design and optimize scalable SQL and Python-based data transformations, algorithms, and analytics solutions that drive operational improvements and strategic business decisions. Architect, build, and maintain batch, micro-batch, and real-time data pipelines using modern ETL/ELT frameworks to integrate data from enterprise systems, cloud platforms, OT systems, and external sources.

Develop advanced business intelligence and reporting solutions using Power BI, SSRS, and related tooling, including semantic models, reusable datasets, and interactive dashboards. Partner with cross-functional stakeholders to rapidly interpret complex requirements and translate them into scalable, high-value analytical tools, visualizations, and data products. Build programmatic and data-driven solutions to enhance Operational Technology, digital manufacturing, and Industry 4.0 initiatives across the organization

Implement and maintain strong data governance practices including data quality monitoring, validation rules, lineage documentation, and schema management across all enterprise data ecosystems. Software and Automation Development Develop automation solutions using scripting technologies such as PowerShell, Python, C#, and PERL to eliminate manual processes and improve system performance and reliability. Maintain and enhance organizational SharePoint sites, ASP.NET Core, and PHP-based dashboards, ensuring stability, secure configuration, and alignment to evolving business operations

Build and support web applications and integration services using modern frameworks including Bootstrap, HTML5, REACT.js, Node.js, ASP.NET Core, Django, PHP, or similar technologies to streamline workflows and system interoperability. Utilize Microsoft Graph API to securely integrate with Microsoft 365 services, enable advanced automation, and extend enterprise collaboration tools. Apply Microsoft Power Platform capabilities, including Power Apps, Power Automate, and Power BI to rapidly develop internal solutions and maximize existing technology investments

Assess business requirements and recommend appropriate development frameworks, architectural patterns, and technologies to ensure scalable and maintainable custom solutions. Evaluate incoming business requirements to identify and recommend the most appropriate development tools and frameworks for each custom solution. Artificial Intelligence and Machine Learning Design, develop, and deploy machine learning and artificial intelligence models tailored to complex business and operational challenges.

Collect, engineer, and prepare large, diverse datasets for model development, ensuring proper handling, labeling, and validation across the full lifecycle. Train, test, and optimize predictive models to achieve high performance, reliability, and scalability using modern ML frameworks and MLOps best practices. Integrate AI/ML models into business applications, APIs, data pipelines, and enterprise platforms to ensure seamless operationalization and measurable value.

Monitor, maintain, and retrain production ML models, implement continuous evaluation, drift detection, and responsible AI governance standards. Technology Leadership and Compliance Maintain and enhance existing scripted reporting and automation tools to ensure their continued alignment with evolving business and technical requirements. Stay informed on emerging data engineering, analytics, AI/ML, automation, and cloud technologies, providing strategic recommendations to guide future technical investments.

Coordinate with enterprise architecture and follow established organizational architectures, development methodologies, and engineering standards, including code quality, secure coding practices, data modeling, design patterns, documentation requirements, and DevSecOps processes. Ensure all data systems, pipelines, custom applications, and integrations operate in full compliance with CMMC and NIST SP 800-171 requirements. Protect Controlled Unclassified Information (CUI) and Federal Contract Information (FCI) using securecoding practices, data governance standards, and cybersecurity-aligned handling procedures.

SKILLS EXPERIENCE EDUCATION: Required Qualifications Bachelors degree in computer science, Data Engineering, Information Technology, Analytics, Data Science, or a related technical field, or an equivalent combination of education and experience. Extensive experience in data engineering, data modeling, and database management using SQL across platforms such as Microsoft SQL Server, Oracle, PostgreSQL, or similar relational database systems. Strong proficiency in object-oriented programming and scripting languages including Python, C#, Java, PHP, R, and familiarity with PERL (beneficial but not required).

Proven expertise in building business intelligence and data visualization solutions using Power BI, Tableau, Qlik, Looker, MicroStrategy, Oracle Analytics, or similar tools, SSRS, and Power Query. Hands on experience developing web applications, managing SharePoint environments, and utilizing the Microsoft Power Platform. Experience leveraging application programming interfaces, specifically Microsoft Graph API, for secure system integrations and workflow automations.

Demonstrated ability to collect, process, and analyze large datasets to support data driven business initiatives. Experience with data ingestion and data integration using tools such as SQL, SSIS, Talend, Boomi, or similar ETL/ELT and integration platforms to build reliable, scalable, and automated data pipelines. Superior analytical and problem-solving skills, with the ability to translate non-technical business requests into technical data solutions.

Excellent communication skills for collaborating with technical teams and business stakeholders. Preferred Qualifications Masters degree in data science, Computer Science, Artificial Intelligence, Analytics, Machine Learning, or closely related technical discipline. Practical experience designing, training, and deploying machine learning models in a live production environment.

Familiarity with modern data workflow management and distributed processing technologies, including Apache Airflow, Prefect, Dagster, Apache Spark, Databricks, or equivalent cloud-native orchestration and compute frameworks. Experience working within the aerospace, defense, or government contracting sectors. Deep understanding of Department of Defense cybersecurity compliance requirements including CMMC, NIST SP 800 171, and ITAR regulations.

Certifications in Microsoft data platforms, cloud architectures, or data engineering specialties. ADDITIONAL INFORMATION: This job description is intended to describe the general nature and level of work being performed. It is not an exhaustive list of all responsibilities, duties, or skills required.

Employees may be required to perform other job-related duties as assigned, consistent with business needs and applicable law. This position requires no security clearance. Due to the nature of our work and applicable U.S

export control laws, this position requires International Traffic in Arms Regulations (ITAR) eligibility. Only individuals who qualify as a U.S. person as defined by ITAR (U.S

citizens, U.S. permanent residents, refugees, or asylees), unless specified otherwise within job description, are eligible for employment. Applied Aerospace and Defense is committed to equal employment opportunity

All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, national origin, age, disability, veteran or military status, or any other characteristic protected by applicable federal, state, or local law. Applicants who require reasonable accommodation for any part of the application or hiring process due to disability, medical condition, or other protected reason may contact the Human Resources Department. Requests will be reviewed in accordance with applicable law.

Where required by law, the applicable pay range and a summary of benefits and other compensation for this position will be provided.