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Mid-Level Dev Ops Engineer, Manager, Finance Analytics
jobright.com, Stamford, Connecticut, United States, 06925
Mid-Level Dev Ops Engineer, Manager, Finance Analytics
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Mid-Level Dev Ops Engineer, Manager, Finance Analytics
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Jobright.ai Mid-Level Dev Ops Engineer, Manager, Finance Analytics
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Mid-Level Dev Ops Engineer, Manager, Finance Analytics
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Jobright.ai Jobright is an AI-powered career platform that helps job seekers discover the top opportunities in the US. We are NOT a staffing agency. Jobright does not hire directly for these positions. We connect you with verified openings from employers you can trust. Job Summary: Webster Bank is a leading commercial bank that prioritizes putting people first and helping them achieve their financial goals. They are seeking a Dev Ops Engineer with a focus on finance analytics to design, deploy, and maintain serverless infrastructure, build CI/CD pipelines, and support data workflows while collaborating across teams to implement effective solutions. Responsibilities: Develop expert knowledge and experience with Websters data systems and tools. Design, deploy, and maintain serverless infrastructure and model pipelines. Designing, building, and maintaining infrastructure. Execute and support CECL Quarterly Production Process and Annual Refresh. Build, automate, and monitor statistical and machine learning model workflows from development to production. Analyze and organize systems and datasets to derive actionable insights and create efficient and low maintenance pipelines. Develop data workflows to support data ingestion, wrangling, transformation, reporting and dashboarding. Build and manage CI/CD pipelines to ensure reliable, secure, and repeatable deployments. Collaborate across teams to analyze requirements and propose infrastructure or pipeline solutions. Use Snowflake for data access and processing, including creating robust data pipelines and integrations. Manage data science notebooks in production environments (e.g., SageMaker Studio,JupyterHub). Use Git for version control and workflow management across codebases and projects. Collaborate with cross-functional teams to understand data requirements and implement effective solutions. Qualifications: Required: 5+ years of experience working in data engineering and/or DevOps specializing in AI and Machine Learning deployment. Experience working with complex data structures within a RDMS (Oracle, SQL). Experience in core programming languages and data science packages (Python, Keras, Tensorflow, PyTorch, Pandas, Scikit-learn, Jupyter, etc.) Proficient in Python/SAS Programming Language. Experience with traditional ML and deep learning techniques (CNNs, RNNs, LSTMs, GANs), model tuning, and validation of developed algorithms. Familiarity with commercial & consumer banking products, operations, and processes, or risk & finance background/experience. 5+ years of experience leveraging cloud services and capabilities of computing platforms (e.g., AWS SageMaker, S3, EC2, Redshift, Athena, Glue, Lambda, etc. or Azure/GCP equivalent). Experience in Reporting and Dashboarding tools (e.g.- Tableau, Qlik Sense). Extensive experience with design, coding, and testing patterns as well as engineering software platforms and large-scale data infrastructures. Experience in DevOps and leveraging CI/CD services: Airflow, GitLab, Terraform, Jenkins, etc. Experience with Data Science project implementation. Experience in documenting processes, scripts, memos clearly for internal knowledge sharing and audits. Strong analytical and problem-solving skills and ability to work in a collaborative team environment. Excellent communication skills to convey complex technical concepts to non-technical stakeholders. Ingenuity, analytical thinking, resourceful, persistent, pragmatic, motivated and socially intelligent. Time management skills are needed to prioritize multiple tasks. Bachelors, Masters or Ph.D. degree in computer science, data science or other STEM fields (e.g., physics, math, engineering, etc.) Other degrees with a strong computer science and/or data science background also acceptable. Preferred: Familiarity with Docker and Kubernetes for containerized deployments. Experience with Terraform, AWS CDK, or other infrastructure-as-code tools. Knowledge of ETL/ELT pipelines and orchestration tools. Understanding of monitoring/logging best practices in cloud-based environments. Familiarity with the SAS programming language. Experience using Confluence for documentation and collaboration. Knowledge of Tidal or other workflow automation and scheduling tools. Experience in developing constructive relationships with a wide range of different stakeholders. Experience in developing Machine Learning and Deep Learning models. Ability to independently gather data from various sources and conduct research. Ability to think 'out of the box' and provide suggestions on ways to improve the process. Company: Webster is a commercial bank that provides financial services to corporations, individuals, families, and partners. Founded in 1935, the company is headquartered in Waterbury, Connecticut, USA, with a team of 1001-5000 employees. The company is currently Public Company. Webster Bank has a track record of offering H1B sponsorships. Seniority level
Seniority level
Mid-Senior level Employment type
Employment type
Full-time Job function
Industries
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Join to apply for the
Mid-Level Dev Ops Engineer, Manager, Finance Analytics
role at
Jobright.ai Mid-Level Dev Ops Engineer, Manager, Finance Analytics
1 day ago Be among the first 25 applicants Join to apply for the
Mid-Level Dev Ops Engineer, Manager, Finance Analytics
role at
Jobright.ai Jobright is an AI-powered career platform that helps job seekers discover the top opportunities in the US. We are NOT a staffing agency. Jobright does not hire directly for these positions. We connect you with verified openings from employers you can trust. Job Summary: Webster Bank is a leading commercial bank that prioritizes putting people first and helping them achieve their financial goals. They are seeking a Dev Ops Engineer with a focus on finance analytics to design, deploy, and maintain serverless infrastructure, build CI/CD pipelines, and support data workflows while collaborating across teams to implement effective solutions. Responsibilities: Develop expert knowledge and experience with Websters data systems and tools. Design, deploy, and maintain serverless infrastructure and model pipelines. Designing, building, and maintaining infrastructure. Execute and support CECL Quarterly Production Process and Annual Refresh. Build, automate, and monitor statistical and machine learning model workflows from development to production. Analyze and organize systems and datasets to derive actionable insights and create efficient and low maintenance pipelines. Develop data workflows to support data ingestion, wrangling, transformation, reporting and dashboarding. Build and manage CI/CD pipelines to ensure reliable, secure, and repeatable deployments. Collaborate across teams to analyze requirements and propose infrastructure or pipeline solutions. Use Snowflake for data access and processing, including creating robust data pipelines and integrations. Manage data science notebooks in production environments (e.g., SageMaker Studio,JupyterHub). Use Git for version control and workflow management across codebases and projects. Collaborate with cross-functional teams to understand data requirements and implement effective solutions. Qualifications: Required: 5+ years of experience working in data engineering and/or DevOps specializing in AI and Machine Learning deployment. Experience working with complex data structures within a RDMS (Oracle, SQL). Experience in core programming languages and data science packages (Python, Keras, Tensorflow, PyTorch, Pandas, Scikit-learn, Jupyter, etc.) Proficient in Python/SAS Programming Language. Experience with traditional ML and deep learning techniques (CNNs, RNNs, LSTMs, GANs), model tuning, and validation of developed algorithms. Familiarity with commercial & consumer banking products, operations, and processes, or risk & finance background/experience. 5+ years of experience leveraging cloud services and capabilities of computing platforms (e.g., AWS SageMaker, S3, EC2, Redshift, Athena, Glue, Lambda, etc. or Azure/GCP equivalent). Experience in Reporting and Dashboarding tools (e.g.- Tableau, Qlik Sense). Extensive experience with design, coding, and testing patterns as well as engineering software platforms and large-scale data infrastructures. Experience in DevOps and leveraging CI/CD services: Airflow, GitLab, Terraform, Jenkins, etc. Experience with Data Science project implementation. Experience in documenting processes, scripts, memos clearly for internal knowledge sharing and audits. Strong analytical and problem-solving skills and ability to work in a collaborative team environment. Excellent communication skills to convey complex technical concepts to non-technical stakeholders. Ingenuity, analytical thinking, resourceful, persistent, pragmatic, motivated and socially intelligent. Time management skills are needed to prioritize multiple tasks. Bachelors, Masters or Ph.D. degree in computer science, data science or other STEM fields (e.g., physics, math, engineering, etc.) Other degrees with a strong computer science and/or data science background also acceptable. Preferred: Familiarity with Docker and Kubernetes for containerized deployments. Experience with Terraform, AWS CDK, or other infrastructure-as-code tools. Knowledge of ETL/ELT pipelines and orchestration tools. Understanding of monitoring/logging best practices in cloud-based environments. Familiarity with the SAS programming language. Experience using Confluence for documentation and collaboration. Knowledge of Tidal or other workflow automation and scheduling tools. Experience in developing constructive relationships with a wide range of different stakeholders. Experience in developing Machine Learning and Deep Learning models. Ability to independently gather data from various sources and conduct research. Ability to think 'out of the box' and provide suggestions on ways to improve the process. Company: Webster is a commercial bank that provides financial services to corporations, individuals, families, and partners. Founded in 1935, the company is headquartered in Waterbury, Connecticut, USA, with a team of 1001-5000 employees. The company is currently Public Company. Webster Bank has a track record of offering H1B sponsorships. Seniority level
Seniority level
Mid-Senior level Employment type
Employment type
Full-time Job function
Industries
Software Development Referrals increase your chances of interviewing at Jobright.ai by 2x Inferred from the description for this job
Medical insurance Vision insurance 401(k) Get notified about new DevOps Engineer jobs in
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