DevOps Manager

If you’re looking for a meaningful career, you’ll find it here at Webster. Founded in 1935, our focus has always been to put people first doing whatever we can to help individuals, families, businesses and our colleagues achieve their financial goals. As a leading commercial bank, we remain passionate about serving our clients and supporting our communities. Integrity, Collaboration, Accountability, Agility, Respect, Excellence are Webster’s values, these set us apart as a bank and as an employer.

Come join our team where you can expand your career potential, benefit from our robust development opportunities, and enjoy meaningful work!

The role involves working with Webster’s data systems and tools to design, implement, configure, maintain hardware, software, and data pipelines for Finance Analytics (FAST). Ability to anticipate and resolve challenges, generate clear action plans and communicate results. The individual will collaborate closely with data scientists and analysts to build ML and statistical model pipelines, integrate tools, and manage infrastructure that supports production-ready data science solutions. A key part of this role involves effective communication with stakeholders-you should be able to clearly present technical solutions, infrastructure proposals, and deployment strategies to both technical and non-technical teams.

Job Summary :

The role involves working with Webster’s data systems and tools to design, implement, configure, maintain hardware, software, and data pipelines for Finance Analytics (FAST). Ability to anticipate and resolve challenges, generate clear action plans and communicate results. The individual will collaborate closely with data scientists and analysts to build ML and statistical model pipelines, integrate tools, and manage infrastructure that supports production-ready data science solutions. A key part of this role involves effective communication with stakeholders-you should be able to clearly present technical solutions, infrastructure proposals, and deployment strategies to both technical and non-technical teams.

Primary responsibilities :

Develop expert knowledge and experience with Webster’s 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 (, 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.

Key Skills / Experience :

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.)

Experience working with complex data structures within a RDMS (Oracle, SQL).

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 (, AWS SageMaker, S3, EC2, Redshift, Athena, Glue, Lambda, etc. or Azure / GCP equivalent).

Experience in Reporting and Dashboarding tools ( 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.

Desired Attributes :

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.

Education :

Bachelors, Masters’ or degree in computer science, data science or other STEM fields (, physics, math, engineering, etc.) Other degrees with a strong computer science and / or data science background also acceptable.

The estimated base salary range for this position is $110,000 USD to $125,000 USD. Actual salary may vary up or down depending on job-related factors which may include knowledge, skills, experience, and location. In addition, this position is eligible for incentive compensation.

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Webster Financial Corporation and its subsidiaries (“Webster”) are equal opportunity employers that are committed to sustaining an inclusive environment. All qualified applicants will receive consideration for employment without regard to race, color, religion, age, marital status, national origin, ancestry, citizenship, sex, sexual orientation, gender identity and / or expression, physical or mental disability, protected veteran status, or any other characteristic protected by law.