3 Data masking Jobs in India

LEAD DATA SECURITY SOLUTION ENGINEER

Experience: 10+ Years

Location: Remote

Employment Type: Full-Time

Budget: Up to ₹35 LPA

Time Zone: US Eastern Time (ET)

Shift: US ET Night Shift

Job Description

We are looking for an experienced Lead Data Security Solution Engineer with strong expertise in database security, IAM, authentication, authorization, and enterprise data architecture.

The candidate will be responsible for assessing existing database environments, designing secure data access architectures, implementing fine-grained authorization controls, and ensuring licensed data is protected throughout its lifecycle.

The role involves working closely with database, IAM, security, infrastructure, application, data platform, and governance teams.

Key Responsibilities

1. Technical and Database Assessment

• Assess database platforms, schemas, data flows, data lineage, connectivity, and downstream dependencies.
• Review where licensed data is stored, transformed, replicated, extracted, cached, archived, and backed up.
• Evaluate existing database security capabilities and identify gaps, risks, and technical constraints.

2. Authentication and Identity Integration

• Design secure authentication for users, applications, service identities, and workloads.
• Implement or evaluate OAuth 2.0, OIDC, token-based authentication, and enterprise IAM integration.
• Integrate enterprise identities, security groups, database roles, and policy engines.
• Reduce dependency on shared and long-lived credentials.

3. Fine-Grained Authorization and Data Security

• Design and implement database-level access controls.
• Implement Row-Level Security (RLS), Column-Level Security (CLS), dynamic data masking, and policy-based filtering.
• Design secure isolation patterns for licensed datasets.
• Ensure security policies are enforced at the database layer.

4. Auditing, Monitoring, and Traceability

• Design database auditing and activity monitoring.
• Track user access, queries, exports, permission changes, and privileged activities.
• Integrate audit logs with centralized monitoring and reporting systems.
• Define audit retention and investigation requirements.

5. Data Lifecycle and Deletion

• Design access revocation mechanisms for users, projects, and expired licensing agreements.
• Define secure data deletion processes across databases, backups, archives, caches, and downstream systems.
• Ensure deletion activities are validated and supported by audit evidence.

6. Solution Architecture and Engineering

• Develop current-state and target-state security architectures.
• Prepare technical specifications, implementation plans, and reusable security patterns.
• Evaluate solution options based on security, scalability, performance, feasibility, and cost.
• Collaborate with cross-functional technical and business teams.

7. POC Design and Execution

• Design and execute Proof of Concepts (POCs) for database security scenarios.
• Validate authentication, authorization, data isolation, auditing, access revocation, and deletion.
• Document test results, technical limitations, recommendations, and implementation approaches.

Required Technical Skills

• 10+ years of experience in database engineering, data security, solution architecture, or related fields.
• Strong hands-on experience with relational databases, SQL, database architecture, schemas, roles, and privileges.
• Experience implementing Row-Level Security (RLS), Column-Level Security (CLS), dynamic masking, and fine-grained authorization.
• Strong understanding of IAM, OAuth 2.0, OIDC, token-based authentication, service identities, and workload identities.
• Experience with secrets management and secure database connectivity.
• Knowledge of database auditing, query monitoring, centralized logging, alerting, and security investigations.
• Experience securing integrations involving applications, APIs, analytical tools, and ETL/ELT pipelines.
• Understanding of data lineage, retention, lifecycle management, revocation, deletion, backup, and recovery.
• Ability to assess heterogeneous database platforms and recommend suitable security architectures.
• Strong architecture, troubleshooting, documentation, and stakeholder-management skills.

Nice to Have

• Experience with enterprise data platforms and cloud or hybrid database environments.
• Knowledge of data catalogs, access governance, and policy-enforcement technologies.
• Experience in pharmaceutical research, healthcare, scientific data, or intellectual property protection.
• Exposure to data licensing, contractual-use restrictions, and regulated environments.
• Experience designing and executing security POCs and implementing production-ready solutions.

Expected Deliverables

• Database security and capability assessment.
• Current-state and target-state security architecture.
• Database authentication and IAM integration design.
• Fine-grained authorization and data-masking design.
• Data firewalling and licensed-dataset isolation patterns.
• Audit, monitoring, and traceability framework.
• Data revocation, retention, and deletion strategy.
• Technical feasibility, gap, dependency, and risk assessments.
• POC implementation, test results, and recommendations.
• Reusable technical documentation and operational handover.

Work Requirements

• Fully remote opportunity.
• Full-time employment.
• Must be comfortable working in the US Eastern Time (ET) night shift.
• Budget: Up to ₹35 LPA.

JOB DETAILS:

* Job Title: Associate III - Data Engineering

* Industry: Global digital transformation solutions provide

* Salary: Best in Industry

* Experience: 4-6 years

* Location: Trivandrum, Kochi

Job Description

Job Title:

Data Services Engineer – AWS & Snowflake

Job Summary:

As a Data Services Engineer, you will be responsible for designing, developing, and maintaining robust data solutions using AWS cloud services and Snowflake.

You will work closely with cross-functional teams to ensure data is accessible, secure, and optimized for performance.

Your role will involve implementing scalable data pipelines, managing data integration, and supporting analytics initiatives.

Responsibilities:

• Design and implement scalable and secure data pipelines on AWS and Snowflake (Star/Snowflake schema)

• Optimize query performance using clustering keys, materialized views, and caching

• Develop and maintain Snowflake data warehouses and data marts.

• Build and maintain ETL/ELT workflows using Snowflake-native features (Snowpipe, Streams, Tasks).

• Integrate Snowflake with cloud platforms (AWS, Azure, GCP) and third-party tools (Airflow, dbt, Informatica)

• Utilize Snowpark and Python/Java for complex transformations

• Implement RBAC, data masking, and row-level security.

• Optimize data storage and retrieval for performance and cost-efficiency.

• Collaborate with stakeholders to gather data requirements and deliver solutions.

• Ensure data quality, governance, and compliance with industry standards.

• Monitor, troubleshoot, and resolve data pipeline and performance issues.

• Document data architecture, processes, and best practices.

• Support data migration and integration from various sources.

Qualifications:

• Bachelor’s degree in Computer Science, Information Technology, or a related field.

• 3 to 4 years of hands-on experience in data engineering or data services.

• Proven experience with AWS data services (e.g., S3, Glue, Redshift, Lambda).

• Strong expertise in Snowflake architecture, development, and optimization.

• Proficiency in SQL and Python for data manipulation and scripting.

• Solid understanding of ETL/ELT processes and data modeling.

• Experience with data integration tools and orchestration frameworks.

• Excellent analytical, problem-solving, and communication skills.

Preferred Skills:

• AWS Glue, AWS Lambda, Amazon Redshift

• Snowflake Data Warehouse

• SQL & Python

Skills: Aws Lambda, AWS Glue, Amazon Redshift, Snowflake Data Warehouse

Must-Haves

AWS data services (4-6 years), Snowflake architecture (4-6 years), SQL (proficient), Python (proficient), ETL/ELT processes (solid understanding)

Skills: AWS, AWS lambda, Snowflake, Data engineering, Snowpipe, Data integration tools, orchestration framework

Relevant 4 - 6 Years

python is mandatory

******

Notice period - 0 to 15 days only (Feb joiners’ profiles only)

Location: Kochi

F2F Interview 7th Feb

ROLES AND RESPONSIBILITIES:

You will be responsible for architecting, implementing, and optimizing Dremio-based data Lakehouse environments integrated with cloud storage, BI, and data engineering ecosystems. The role requires a strong balance of architecture design, data modeling, query optimization, and governance enablement in large-scale analytical environments.

• Design and implement Dremio lakehouse architecture on cloud (AWS/Azure/Snowflake/Databricks ecosystem).
• Define data ingestion, curation, and semantic modeling strategies to support analytics and AI workloads.
• Optimize Dremio reflections, caching, and query performance for diverse data consumption patterns.
• Collaborate with data engineering teams to integrate data sources via APIs, JDBC, Delta/Parquet, and object storage layers (S3/ADLS).
• Establish best practices for data security, lineage, and access control aligned with enterprise governance policies.
• Support self-service analytics by enabling governed data products and semantic layers.
• Develop reusable design patterns, documentation, and standards for Dremio deployment, monitoring, and scaling.
• Work closely with BI and data science teams to ensure fast, reliable, and well-modeled access to enterprise data.

IDEAL CANDIDATE:

• Bachelor’s or Master’s in Computer Science, Information Systems, or related field.
• 5+ years in data architecture and engineering, with 3+ years in Dremio or modern lakehouse platforms.
• Strong expertise in SQL optimization, data modeling, and performance tuning within Dremio or similar query engines (Presto, Trino, Athena).
• Hands-on experience with cloud storage (S3, ADLS, GCS), Parquet/Delta/Iceberg formats, and distributed query planning.
• Knowledge of data integration tools and pipelines (Airflow, DBT, Kafka, Spark, etc.).
• Familiarity with enterprise data governance, metadata management, and role-based access control (RBAC).
• Excellent problem-solving, documentation, and stakeholder communication skills.

PREFERRED:

• Experience integrating Dremio with BI tools (Tableau, Power BI, Looker) and data catalogs (Collibra, Alation, Purview).
• Exposure to Snowflake, Databricks, or BigQuery environments.
• Experience in high-tech, manufacturing, or enterprise data modernization programs.