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SENIOR INFORMATION SECURITY ENGINEER (DEVSECOPS)

Key Skills: Software Development Life Cycle (SDLC), CI/CD

About Company: Consumer Internet / E-Commerce

Company Size: Mid-Sized

Experience Required: 6 - 10 years

Working Days: 5 days/week

Office Location: Bengaluru [Karnataka]

Review Criteria:

Mandatory:

• Strong DevSecOps profile
• Must have 5+ years of hands-on experience in Information Security, with a primary focus on cloud security across AWS, Azure, and GCP environments.
• Must have strong practical experience working with Cloud Security Posture Management (CSPM) tools such as Prisma Cloud, Wiz, or Orca along with SIEM / IDS / IPS platforms
• Must have proven experience in securing Kubernetes and containerized environments including image security,runtime protection, RBAC, and network policies.
• Must have hands-on experience integrating security within CI/CD pipelines using tools such as Snyk, GitHub Advanced Security,or equivalent security scanning solutions.
• Must have solid understanding of core security domains including network security, encryption, identity and access management key management, and security governance including cloud-native security services like GuardDuty, Azure Security Center etc
• Must have practical experience with Application Security Testing tools including SAST, DAST, and SCA in real production environments
• Must have hands-on experience with security monitoring, incident response, alert investigation, root-cause analysis (RCA), and managing VAPT / penetration testing activities
• Must have experience securing infrastructure-as-code and cloud deployments using Terraform, CloudFormation, ARM, Docker, and Kubernetes
• B2B SaaS Product companies
• Must have working knowledge of globally recognized security frameworks and standards such as ISO 27001, NIST, and CIS with exposure to SOC2, GDPR, or HIPAA compliance environments

Preferred:

• Experience with DevSecOps automation, security-as-code, and policy-as-code implementations
• Exposure to threat intelligence platforms, cloud security monitoring, and proactive threat detection methodologies, including EDR / DLP or vulnerability management tools
• Must demonstrate strong ownership mindset, proactive security-first thinking, and ability to communicate risks in clear business language

Roles & Responsibilities:

We are looking for a Senior Information Security Engineer who can help protect our cloud infrastructure, applications, and data while enabling teams to move fast and build securely.

This role sits deep within our engineering ecosystem. You’ll embed security into how we design, build, deploy, and operate systems—working closely with Cloud, Platform, and Application Engineering teams. You’ll balance proactive security design with hands-on incident response, and help shape a strong, security-first culture across the organization.

If you enjoy solving real-world security problems, working close to systems and code, and influencing how teams build securely at scale, this role is for you.

What You’ll Do-

Cloud & Infrastructure Security:

• Design, implement, and operate cloud-native security controls across AWS, Azure, GCP, and Oracle.
• Strengthen IAM, network security, and cloud posture using services like GuardDuty, Azure Security Center and others.
• Partner with platform teams to secure VPCs, security groups, and cloud access patterns.

Application & DevSecOps Security:

• Embed security into the SDLC through threat modeling, secure code reviews, and security-by-design practices.
• Integrate SAST, DAST, and SCA tools into CI/CD pipelines.
• Secure infrastructure-as-code and containerized workloads using Terraform, CloudFormation, ARM, Docker, and Kubernetes.

Security Monitoring & Incident Response:

• Monitor security alerts and investigate potential threats across cloud and application layers.
• Lead or support incident response efforts, root-cause analysis, and corrective actions.
• Plan and execute VAPT and penetration testing engagements (internal and external), track remediation, and validate fixes.
• Conduct red teaming activities and tabletop exercises to test detection, response readiness, and cross-team coordination.
• Continuously improve detection, response, and testing maturity.

Security Tools & Platforms:

• Manage and optimize security tooling including firewalls, SIEM, EDR, DLP, IDS/IPS, CSPM, and vulnerability management platforms.
• Ensure tools are well-integrated, actionable, and aligned with operational needs.

Compliance, Governance & Awareness:

• Support compliance with industry standards and frameworks such as SOC2, HIPAA, ISO 27001, NIST, CIS, and GDPR.
• Promote secure engineering practices through training, documentation, and ongoing awareness programs.
• Act as a trusted security advisor to engineering and product teams.

Continuous Improvement:

• Stay ahead of emerging threats, cloud vulnerabilities, and evolving security best practices.
• Continuously raise the bar on a company's security posture through automation and process improvement.

Endpoint Security (Secondary Scope):

• Provide guidance on endpoint security tooling such as SentinelOne and Microsoft Defender when required.

Ideal Candidate:

• Strong hands-on experience in cloud security across AWS and Azure.
• Practical exposure to CSPM tools (e.g., Prisma Cloud, Wiz, Orca) and SIEM / IDS / IPS platforms.
• Experience securing containerized and Kubernetes-based environments.
• Familiarity with CI/CD security integrations (e.g., Snyk, GitHub Advanced Security, or similar).
• Solid understanding of network security, encryption, identity, and access management.
• Experience with application security testing tools (SAST, DAST, SCA).
• Working knowledge of security frameworks and standards such as ISO 27001, NIST, and CIS.
• Strong analytical, troubleshooting, and problem-solving skills.

Nice to Have:

• Experience with DevSecOps automation and security-as-code practices.
• Exposure to threat intelligence and cloud security monitoring solutions.
• Familiarity with incident response frameworks and forensic analysis.
• Security certifications such as CISSP, CISM, CCSP, or CompTIA Security+.

Perks, Benefits and Work Culture:

A wholesome opportunity in a fast-paced environment that will enable you to juggle between concepts, yet maintain the quality of content, interact and share your ideas and have loads of learning while at work. Work with a team of highly talented young professionals and enjoy the comprehensive benefits that company offers.

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.

Review Criteria

• Strong Dremio / Lakehouse Data Architect profile
• 5+ years of experience in Data Architecture / Data Engineering, with minimum 3+ years hands-on in Dremio
• Strong expertise in SQL optimization, data modeling, query performance tuning, and designing analytical schemas for large-scale systems
• Deep experience with cloud object storage (S3 / ADLS / GCS) and file formats such as Parquet, Delta, Iceberg along with distributed query planning concepts
• Hands-on experience integrating data via APIs, JDBC, Delta/Parquet, object storage, and coordinating with data engineering pipelines (Airflow, DBT, Kafka, Spark, etc.)
• Proven experience designing and implementing lakehouse architecture including ingestion, curation, semantic modeling, reflections/caching optimization, and enabling governed analytics
• Strong understanding of data governance, lineage, RBAC-based access control, and enterprise security best practices
• Excellent communication skills with ability to work closely with BI, data science, and engineering teams; strong documentation discipline
• Candidates must come from enterprise data modernization, cloud-native, or analytics-driven companies

Preferred

• Preferred (Nice-to-have) – Experience integrating Dremio with BI tools (Tableau, Power BI, Looker) or data catalogs (Collibra, Alation, Purview); familiarity with Snowflake, Databricks, or BigQuery environments

Job Specific Criteria

• CV Attachment is mandatory
• How many years of experience you have with Dremio?
• Which is your preferred job location (Mumbai / Bengaluru / Hyderabad / Gurgaon)?
• Are you okay with 3 Days WFO?
• Virtual Interview requires video to be on, are you okay with it?

Role & 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.