Associate Principal Engineer
Nagarro · IT Services & Consulting
- Hyderabad, India
- On-site
- Posted today
- Software Engineering
- Full-time
About the job
👋🏼We're Nagarro.
We are a Digital Product Engineering company that is scaling in a big way! We build products, services, and experiences that inspire, excite, and delight. We work at a scale — across all devices and digital mediums, and our people exist everywhere in the world (18500+ experts across 39 countries, to be exact). Our work culture is dynamic and non-hierarchical. We are looking for great new colleagues. That is where you come in!
Requirements
Experience : 9+years
Strong experience in data architecture, data engineering, or enterprise data platforms, with substantial hands-on experience in Snowflake.
Strong expertise in Technology Architecture and Data Architecture, including solution design, data modeling, integration, and implementation of scalable enterprise platforms.
Strong hands-on experience with Snowflake security, data governance frameworks, access management, and compliance controls.
Proficiency in Snowflake Row Access Policies (RAP), Role-Based Access Control (RBAC), role hierarchies, least-privilege permissions, dynamic data masking, and tag-based masking policies.
Experience enforcing access controls at database, schema, object, row, and column levels.
Strong understanding of data ownership, stewardship, classification, metadata management, data lineage, data quality, and audit requirements.
Strong SQL skills, including complex queries, stored procedures, incremental processing, and query performance tuning.
Strong Python programming skills for data processing, API integration, automation, and pipeline development.
Experience with PostgreSQL and enterprise database architecture, including data modeling, integration, and performance optimization.
Hands-on experience with Streamlit application development and Snowflake Cortex capabilities, including Cortex Analyst, Cortex Search, Cortex Agents, and semantic modeling.
Ability to evaluate AI-generated responses and implement appropriate security and governance controls for AI applications.
Experience building and managing data ingestion and transformation pipelines using Azure Data Factory, AWS Glue, Python, or equivalent tools.
Strong understanding of full loads, incremental loads, CDC, data validation, error handling, and pipeline monitoring.
Familiarity with AWS services such as S3 and IAM, including secure integration with Snowflake.
Experience using Git, Azure DevOps, and CI/CD pipelines to version, review, test, and deploy database objects, security policies, and application changes across environments.
Knowledge of data privacy, PII protection, access reviews, audit evidence, data retention, and regulatory compliance requirements.
Strong architectural leadership skills, with the ability to define standards, evaluate design decisions, and guide technical teams toward secure and maintainable solutions.
Excellent communication and stakeholder management skills, with the ability to explain complex architecture, governance, security, and AI concepts to technical and business audiences.
Strong analytical and problem-solving abilities, including the capacity to clarify ambiguous requirements, identify risks, and recommend practical solutions.
Ability to manage multiple initiatives, dependencies, and timelines while collaborating with distributed teams.
Experience mentoring engineers and driving technical excellence across data architecture and engineering teams.
PL/SQL knowledge is desirable.
Relevant Snowflake, cloud, or data architecture certifications are preferred.
Responsibilities
Define, implement, and maintain enterprise data governance standards covering data ownership, stewardship, classification, metadata, lineage, data quality, and compliance.
Design and implement secure, scalable Snowflake data architectures aligned with enterprise architecture and security standards.
Develop and maintain Snowflake Row Access Policies (RAP) to control data visibility based on region, market, business unit, and user entitlements.
Implement Role-Based Access Control (RBAC), role hierarchies, least-privilege access, and database-level permissions.
Protect sensitive and personally identifiable information (PII) using dynamic data masking, tag-based masking policies, and column-level security.
Enforce access controls across database, schema, object, row, and column levels.
Establish access reviews, audit monitoring, secure authentication, and integration practices to meet organizational privacy, retention, and compliance requirements.
Design scalable data models and provide architectural guidance on data integration, SQL optimization, and Snowflake performance tuning.
Develop and optimize SQL and Python solutions for data processing, automation, integration, and incremental data processing.
Build and maintain reliable data ingestion and transformation pipelines using Python, Azure Data Factory, AWS Glue, or equivalent technologies.
Implement full-load, incremental-load, and Change Data Capture (CDC) processes with appropriate data validation, error handling, and pipeline monitoring.
Develop interactive Streamlit applications to enable analytics and conversational access to enterprise data.
Implement Snowflake Cortex Analyst, Cortex Search, Cortex Agents, and semantic models to support natural-language queries, information retrieval, and AI-driven analytics.
Evaluate AI response accuracy and ensure appropriate data governance, security, and access controls within AI-enabled applications.
Analyze Snowflake query profiles, optimize warehouse utilization, and balance performance with cost efficiency.
Automate the deployment of database objects, security policies, and application changes using Git, Azure DevOps, and CI/CD pipelines.
Integrate Snowflake securely with cloud services, including AWS S3 and IAM.
Collaborate with business stakeholders, data owners, security teams, governance teams, and engineering teams to establish and enforce architecture standards.
Lead solution design, assess technical risks, resolve architectural challenges, and guide implementation decisions across enterprise data initiatives.
Mentor engineers, review technical designs, and promote secure, scalable, maintainable, and compliant data solutions.
Manage multiple initiatives, dependencies, and delivery timelines while ensuring alignment with business and technology objectives.
Bachelor’s or master’s degree in computer science, Information Technology, or a related field.