SeniorAdministrator - Data security and compliance,Presales

Job Summary

Design and implement masking policies using Databricks (deterministic, random, shuffling, substitution, key-based, format-preserving), ensuring consistent masking across systems.

• Implement and manage Data Subset strategies (constraint-based, rule-based) and optimize extracts for performance and storage.
• Build and schedule data flow for end-to-end orchestration (extract, mask, validate, publish), including dependencies, parameters, and notifications.
• Perform post-mask validation (row counts, referential integrity checks, key uniqueness, format checks) and reconcile issues with source/application teams.
• Monitor and troubleshoot the job execution (logs, performance bottlenecks, failures) and drive incident/problem resolution through ServiceNow.
• Ensure compliance with data privacy and audit requirements (least privilege access, evidence capture, approvals, retention/cleanup of test extracts).
• Create and maintain reusable masking rule libraries, templates, and standardized runbooks to improve repeatability across applications.
• Coordinate releases and stakeholder communication: refresh windows, downtime impacts, sign-offs, and delivery confirmations.
• Design and build data pipelines using Python to provision test datasets from enterprise sources.

Key Responsibilities

Design and implement masking policies using Databricks (deterministic, random, shuffling, substitution, key-based, format-preserving), ensuring consistent masking across systems.

• Implement and manage Data Subset strategies (constraint-based, rule-based) and optimize extracts for performance and storage.
• Build and schedule data flow for end-to-end orchestration (extract, mask, validate, publish), including dependencies, parameters, and notifications.
• Perform post-mask validation (row counts, referential integrity checks, key uniqueness, format checks) and reconcile issues with source/application teams.
• Monitor and troubleshoot the job execution (logs, performance bottlenecks, failures) and drive incident/problem resolution through ServiceNow.
• Ensure compliance with data privacy and audit requirements (least privilege access, evidence capture, approvals, retention/cleanup of test extracts).
• Create and maintain reusable masking rule libraries, templates, and standardized runbooks to improve repeatability across applications.
• Coordinate releases and stakeholder communication: refresh windows, downtime impacts, sign-offs, and delivery confirmations.
• Design and build data pipelines using Python to provision test datasets from enterprise sources.

Skill Requirements

Design and implement masking policies using Databricks (deterministic, random, shuffling, substitution, key-based, format-preserving), ensuring consistent masking across systems.

• Implement and manage Data Subset strategies (constraint-based, rule-based) and optimize extracts for performance and storage.
• Build and schedule data flow for end-to-end orchestration (extract, mask, validate, publish), including dependencies, parameters, and notifications.
• Perform post-mask validation (row counts, referential integrity checks, key uniqueness, format checks) and reconcile issues with source/application teams.
• Monitor and troubleshoot the job execution (logs, performance bottlenecks, failures) and drive incident/problem resolution through ServiceNow.
• Ensure compliance with data privacy and audit requirements (least privilege access, evidence capture, approvals, retention/cleanup of test extracts).
• Create and maintain reusable masking rule libraries, templates, and standardized runbooks to improve repeatability across applications.
• Coordinate releases and stakeholder communication: refresh windows, downtime impacts, sign-offs, and delivery confirmations.
• Design and build data pipelines using Python to provision test datasets from enterprise sources.

Other Requirements

Design and implement masking policies using Databricks (deterministic, random, shuffling, substitution, key-based, format-preserving), ensuring consistent masking across systems.

• Implement and manage Data Subset strategies (constraint-based, rule-based) and optimize extracts for performance and storage.
• Build and schedule data flow for end-to-end orchestration (extract, mask, validate, publish), including dependencies, parameters, and notifications.
• Perform post-mask validation (row counts, referential integrity checks, key uniqueness, format checks) and reconcile issues with source/application teams.
• Monitor and troubleshoot the job execution (logs, performance bottlenecks, failures) and drive incident/problem resolution through ServiceNow.
• Ensure compliance with data privacy and audit requirements (least privilege access, evidence capture, approvals, retention/cleanup of test extracts).
• Create and maintain reusable masking rule libraries, templates, and standardized runbooks to improve repeatability across applications.
• Coordinate releases and stakeholder communication: refresh windows, downtime impacts, sign-offs, and delivery confirmations.
• Design and build data pipelines using Python to provision test datasets from enterprise sources.