Senior Data & Automation Engineer

Uniphore is one of the largest B2B AI-native companies—decades-proven, built-for-scale and designed for the enterprise. The company drives business outcomes, across multiple industry verticals, and enables the largest global deployments.

Uniphore infuses AI into every part of the enterprise that impacts the customer. We deliver the only multimodal architecture centered on customers that combines Generative AI, Knowledge AI, Emotion AI, workflow automation and a co-pilot to guide you. We understand better than anyone how to capture voice, video and text and how to analyze all types of data.

As AI becomes more powerful, every part of the enterprise that impacts the customer will be disrupted. We believe the future will run on the connective tissue between people, machines and data: all in the service of creating the most human processes and experiences for customers and employees.

Job Description:

Uniphore is one of the largest B2B AI-native companies decades-proven, built-for-scale and designed for the enterprise. The company drives business outcomes, across multiple industry verticals, and enables the largest global deployments.

Uniphore infuses AI into every part of the enterprise that impacts the customer. We deliver the only multimodal architecture centered on customers that combines Generative AI, Knowledge AI, Emotion AI, workflow automation and a co-pilot to guide you. We understand better than anyone how to capture voice, video and text and how to analyze all types of data.

As AI becomes more powerful, every part of the enterprise that impacts the customer will be disrupted. We believe the future will run on the connective tissue between people, machines and data: all in the service of creating the most human processes and experiences for customers and employees.

Overall Experience: 8 to 10 years

Certification: One of the following is good to have, or equivalent demonstrable experience AWS Certified Data Engineer Associate, Microsoft Certified: Azure Data Engineer Associate, or Google Professional Data Engineer.

Role Requirement

• Strong understanding of data pipeline architecture, ETL/ELT design, and distributed data processing concepts.
• Proficiency in SQL/NoSQL and at least one programming language (Webhook/Python preferred).
• Hands-on experience with a cloud data platforms like Snowflake or Rivery.
• Working experience in building dashboards using Tableau or PowerBi.
• Working knowledge of workflow orchestration tools.
• Understanding of data warehousing concepts, dimensional data modeling (star/snowflake schema), and data quality frameworks.
• Familiarity with Git-based version control and CI/CD practices applied to data pipelines.
• Exposure to containerization (Docker/Kubernetes) and infrastructure-as-code is an advantage.

Job Requirements

Key Accountabilities

• Design, build, and maintain scalable, reliable ETL/ELT pipelines to ingest, transform, and load data from diverse structured and unstructured sources.
• Automate repetitive data-processing, reporting, and operational workflows using Workato or scripting tools to reduce manual effort and turnaround time.
• Develop and maintain data models, schemas, and data warehouse/lakehouse structures that support analytics, reporting, and downstream AI/ML use cases.
• Monitor pipeline and automation health, proactively troubleshoot failures, and resolve issues within agreed SLA timelines.
• Implement data quality checks, validation rules, logging, and alerting to ensure accuracy and reliability of automated data flows.
• Integrate tools with MCP, API’s or develop a solution into automated data and business workflows.
• Good Knowledge on coding with AI tools like Claude Code or Codex.
• Optimize pipeline performance, query efficiency, and cloud storage/compute costs.
• Collaborate with data scientists, analysts, and business stakeholders to translate requirements into automated, production-grade data solutions.
• Document data flows, pipeline architecture, and automation logic for maintainability and knowledge transfer.
• Ensure adherence to data governance, security, and compliance frameworks (e.g., GDPR, SOC 2, ISO 27001).
• Support ad hoc data requests and continuously identify opportunities to automate manual processes across teams.

Process Skills:

• Work within Agile/Scrum delivery practices, managing tasks and sprints via ticketing systems (e.g., Jira).
• Escalate unresolved technical issues appropriately to platform, infrastructure, or data governance teams.
• Strong team player with the ability to collaborate across data, engineering, and business functions.
• Coordinate with stakeholders across regions, ensuring smooth communication and alignment with global data practices.
• Document technical designs, runbooks, and troubleshooting guides for pipelines and automations.
• Share knowledge with teammates and provide constructive feedback for continuous improvement.
• Stay current with emerging data engineering and automation technologies to improve efficiency and delivery quality.
• Coordinate effectively with third party vendors and platform partners (e.g., cloud providers).
• Ability to work independently with minimal supervision while delivering high-quality outcomes.
• Strong adaptability and multi-tasking skills, able to manage multiple pipelines/projects simultaneously.

Location preference:

India - Chennai Uniphore is an equal opportunity employer committed to diversity in the workplace. We evaluate qualified applicants without regard to race, color, religion, sex, sexual orientation, disability, veteran status, and other protected characteristics.

For more information on how Uniphore uses AI to unify—and humanize—every enterprise experience, please visit www.uniphore.com.