Data Governance Engineer

Who are we?

Bottomline helps businesses transform the way they pay and get paid.

A global leader in business payments and cash management, Bottomline’s secure, comprehensive solutions modernize payments for businesses and financial institutions globally. With over 35 years of experience, moving more than $16 trillion in payments annually, Bottomline is committed to driving impactful results for customers by reimagining business payments and delivering solutions that add to the bottom line.

Culture and Values

Our guiding principles represent the values we demonstrate through working together as a customer-focused business!

Delight Customers

Customer delight is at the heart of who we are. It informs all we do from bringing product innovation to our customers before they ask for it (or think of it) to making sure every interaction exceeds their expectations.

Excellent Execution​​​​​​​

We foster an environment that provides clear direction on what is most important along with the tools and resources to deliver those priorities on time. We are committed to doing what we promised.

Work With and For Each Other

We know we can’t do it alone. The most effective teams come together to accomplish great work by leveraging each other's strengths and rallying around one another to be successful.

Create and Grow Sustained Business Value

Our business model and plan are designed to grow the business and its value for years and decades to come.

Location: Bangalore with hybrid model.

Role Summary

We're seeking a Data Governance Engineer to be the technical backbone of our data and AI operations, ensuring our data Lakehouse environment is secure, compliant, and architected for both governance and high-performance analytics. This role bridges deep technical expertise with practical understanding of data governance, data modelling, database design, security, and privacy requirements, enabling our organization to leverage data and AI responsibly and effectively.

Even if you do not have all the experience we are looking for, please apply, especially if you a looking to take the next step in your career.

What You Will Do

You will design and implement the technical frameworks that keep our data secure, compliant, and accessible to authorized users. Working within our AWS and Snowflake infrastructure you will build and maintain data governance systems, security controls, and privacy-preserving mechanisms that protect sensitive information while enabling analytics and AI capabilities. You will translate regulatory requirements and governance policies into technical implementations, ensuring our data Lakehouse meets both business needs and compliance standards.

You will architect solutions for data classification, access control, lineage tracking, and audit logging. You will work closely with our Data Product Manager, data stewards, data owners and business partners to ensure governance and security considerations are built into data products from the ground up, not bolted on afterward. When new AI use cases emerge, you will assess the technical requirements for responsible implementation, from data privacy to model governance to secure deployment.

Key Responsibilities

• Design and implement data governance frameworks including data cataloging, metadata management, lineage tracking, and quality monitoring
• Build and maintain security controls across our AWS and Snowflake environment, including role-based access controls, data masking, encryption, and network security
• Implement privacy-preserving techniques and ensure compliance with global regulations such as GDPR, CCPA, industry specific and customer specific requirements
• In collaboration with our business experts, develop and enforce data classification schemes and access policies that balance security with usability
• Create technical solutions for data quality monitoring, validation, and remediation
• Build analytics infrastructure and optimize cost and query performance to support business intelligence and AI workloads
• Implement audit logging and monitoring systems to track data access and usage
• Collaborate with data stewards, data owners, data engineers and analysts to ensure governance controls don't impede legitimate data use
• Develop automation for governance processes including access provisioning, compliance reporting, and policy enforcement
• Support AI governance by implementing controls for model data access, feature stores, and responsible AI practices
• Document technical architectures, security protocols, and governance procedures
• Stay current with evolving data privacy regulations and security best practices

 

What You Bring

• 4+ years of experience in data engineering, security engineering, or data governance roles
• Strong hands-on experience with cloud data platforms (AWS, Snowflake, or similar)
• Deep understanding of data governance principles including metadata management, lineage, and data quality
• Solid knowledge of data security practices including encryption, access controls, network security, and authentication
• Experience with data privacy regulations (GDPR, CCPA, HIPAA, etc.) and technical implementation of compliance requirements
• Proficiency in SQL and at least one programming language (e.g. Python, Java)
• Understanding of analytics architectures and performance optimization techniques
• Ability to translate business and compliance requirements into technical solutions
• Strong problem-solving skills and attention to detail
• Excellent documentation and communication skills for technical and non-technical audiences

 

Required Technical Skills

 

• Snowflake (security features, governance capabilities, performance tuning)
• AWS services
• SQL (advanced queries, optimization)
• Python or similar scripting language
• Git and version control
• Data modeling and database design

 

Nice to Have

• Certifications in cloud security (AWS Security Specialty, etc.) or privacy (CIPT, CIPP)
• Experience with data governance tools
• Knowledge of AI/ML governance and responsible AI practices
• Experience with data masking, tokenization, and differential privacy techniques
• Familiarity with data Lakehouse architectures and modern data stack tools
• Background in analytics engineering or business intelligence
• Experience with compliance frameworks (SOC 2, ISO 27001, etc.)