Job Summary
Experience – 10+ years of experience Must have Skills: Databricks, Python, Data masking Good to have Skills: IICS, Informatica TDM Job Description: • Configure and maintain Data masking projects on Databricks • 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
Experience – 10+ years of experience Must have Skills: Databricks, Python, Data masking Good to have Skills: IICS, Informatica TDM Job Description: • Configure and maintain Data masking projects on Databricks • 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
Experience – 10+ years of experience Must have Skills: Databricks, Python, Data masking Good to have Skills: IICS, Informatica TDM Job Description: • Configure and maintain Data masking projects on Databricks • 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
Experience – 10+ years of experience Must have Skills: Databricks, Python, Data masking Good to have Skills: IICS, Informatica TDM Job Description: • Configure and maintain Data masking projects on Databricks • 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.