Security Data Engineer

Cerebra; Hyderabad; On-site; INR 2,500,000 - 4,200,000; Full time

Job summary

Cerebra is seeking a Security Data Engineer in Hyderabad to design and operate high-throughput data pipelines, graph ingestion, and data governance across security assets. You will work with Neo4j, Cypher, Kafka, Spark, and cloud data warehouses, partnering with DevOps and ML teams to deploy scalable ML-enabled data products.

Ideal candidates have 7–12 years of experience in data engineering with a focus on security telemetry integration, graph data modeling, and enterprise ITSM tooling.

Qualifications

• Experience architecting high-throughput data pipelines (batch & real-time) using Python, PySpark, Spark, Kafka, and cloud warehouses.
• Hands-on graph ingestion, modeling and entity resolution for graph databases (Neo4j, Neptune, Cosmos DB).
• Integration engineering with ITSM/APM platforms (ServiceNow CMDB/APIs, Dynatrace/OpenTelemetry).
• ML/MLOps pipelines: feature pipelines, model registries, data quality validation tools (Great Expectations, MLflow, Vertex/Azure ML).
• Data reconciliation, deduplication, and lineage across assets, identities, vulnerabilities, and CMDB.
• Proficient Python/SQL, CI/CD automation (GitHub Actions, GitLab CI, Azure DevOps).

Skills

Enterprise Data Engineering

Security Knowledge Graph Ingestion

ServiceNow & Dynatrace Integration

ML Engineering & MLOps

Entity Resolution & Data Governance

Python & SQL

CI/CD & DataOps

Tools

Neo4j

Cypher

Graph Ingestion

Kafka

Apache Spark

PySpark

BigQuery

Dataproc

Azure Synapse

Databricks

OpenTelemetry

Dynatrace

ServiceNow CMDB / REST APIs

GCP / AWS / Azure

Job description

Job Description:

Role: Security Data Engineer

Experience: 7 to 12 Years

Notice period: Immediate to 15 days

Location: Hyderabad

Required Technical Skill Set: Security Data Engineering, Security Knowledge Graph Integration (Neo4j / Cypher / Graph Ingestion), ML Engineering / MLOps, Enterprise ITSM & Telemetry Integrations (ServiceNow CMDB / APIs, Dynatrace APM / OpenTelemetry), Cloud Data Pipelines (GCP BigQuery / Dataflow / Azure Synapse / Databricks), Big Data Processing (Apache Spark / Kafka / PySpark), Python / SQL, CI/CD & DataOps

Experience Range: 7 12 Years overall
Technical experience (with 3+ years in data engineering, graph data pipelines, or security/telemetry integration)

Must-Have

(Candidates must demonstrate depth in core data engineering and a combination/blend of the following specialisms)

• Enterprise Data Engineering & Pipelines: Proven experience architecting and building high-throughput batch and real-time streaming data pipelines using Python, PySpark, Apache Spark, Kafka, and Cloud Data Warehouses (GCP BigQuery / Dataproc, Azure Synapse / Databricks, or AWS).
• Security Knowledge Graph Ingestion & Modeling: Hands-on experience building ingestion contracts, graph ETLs, and entity resolution pipelines to populate Graph Databases (Neo4j, Amazon Neptune, Azure Cosmos DB / Gremlin) using Cypher or Gremlin.
• ServiceNow & Dynatrace Integration Engineering: Deep practical experience integrating with enterprise ITSM and APM platforms: extracting configuration items (CIs), relationships, and change data from ServiceNow CMDB / REST APIs, and ingesting telemetry, metrics, spans, and problem events from Dynatrace / OpenTelemetry.
• ML Engineering & MLOps Pipelines: Experience operationalising data pipelines for machine learning models, managing feature pipelines, embeddings storage, model registries, and data quality validation frameworks (e.g., Great Expectations, MLflow, Vertex AI / Azure ML pipelines).
• Entity Resolution & Data Governance: Expertise in data reconciliation, deduplication, identity matching, and lineage tracking across disparate security assets, identities, vulnerabilities, and CMDB records.
• Software Engineering & DataOps: Strong proficiency in Python, advanced SQL, automated testing for data pipelines, and CI/CD automation (GitHub Actions, GitLab CI, Azure DevOps).

Good-to-Have

• Experience with Graph-as-a-Service (GaaS) or Context-as-a-Service architectures supporting LLM agents and GraphRAG pipelines.
• Familiarity with Cyber Security domains (SIEM telemetry, vulnerability management, cloud asset posture/CSPM, MITRE ATT&CK mapping).
• Knowledge of event-driven architectures and message queuing (Kafka, Pub/Sub, Event Hubs).
• Certifications: GCP Professional Data Engineer, Azure Data Engineer Associate, Neo4j Certified Professional, Databricks Certified Data Engineer, or equivalent.