We are looking for a Data Engineer for

Heineken with strong experience in Azure data engineering, Databricks and data lake technologies, along with an understanding of IT Security/Cybersecurity use cases. The ideal candidate is a generalist who can work across security data engineering, analytics, Data Science and emerging GenAI use cases.

Key Requirements:

- Senior Data Engineer with proven experience delivering complex data and analytics solutions in enterprise environments.

- Robust hands-on experience with Data Science, LLMs, Agentic AI frameworks, MCP, and RAG architectures, including designing, building, implementing, and troubleshooting solutions in production.

- Minimum 6 years of hands-on Databricks experience

, including architecture, development, optimization, operations, and support of large-scale data platforms.

- Demonstrated experience working with cybersecurity data and analytics

, translating security requirements into actionable insights, detection capabilities, and reporting.

- Hands-on experience with Microsoft security platforms

, particularly Microsoft Sentinel, Microsoft Defender, and Azure Data Explorer (ADX), including data ingestion, analytics, investigations, and operational use cases.

- Proven ability to lead initiatives end-to-end

, from requirements gathering and solution design through implementation, deployment, and operationalization.

- Ability to mentor and guide junior engineers

, providing technical leadership, coaching, and best-practice recommendations.

- Responsible for performing quality assurance and technical reviews of own work and the work of junior Data Engineers/Data Scientists, ensuring coding standards, solution quality, documentation, and operational readiness.

- Ability to provide concrete examples of delivered solutions

,



technical challenges solved, architecture decisions made, and measurable business or security outcomes.

- Strong ownership mindset with a track record of personally driving implementation

, not only coordinating or overseeing delivery.

Key Responsibilities

- Design, develop and maintain scalable data pipelines for IT Security and Cybersecurity use cases.

- Build and manage data solutions using Azure Data Lake Storage (ADLS/ADLS Gen2), Azure Databricks and Azure data services.

- Ingest, transform and process security data from multiple sources such as SIEM, endpoint, identity, network, cloud and application security platforms.

- Develop Databricks/PySpark solutions for processing and analysing large volumes of security telemetry.

- Work with security logs, alerts, vulnerability data, threat intelligence, authentication data and other security datasets.

- Work with Azure Security services and understand security-related data generated across the Azure/Microsoft security ecosystem.

- Develop data models and curated datasets to support Security Operations, Threat Detection, Risk Analytics and reporting.

- Collaborate with Data Scientists to prepare datasets for machine learning, anomaly detection, behavioural analytics and predictive use cases.

- Support GenAI/LLM/RAG use cases involving security data, knowledge retrieval and intelligent security analytics.

- Develop automation scripts using Python Build and maintain Power BI dashboards and reports for security metrics, trends, risks and operational KPIs.

- Implement data quality, governance, access controls and monitoring across data pipelines. Troubleshoot data ingestion, transformation and pipeline issues and optimize performance and cost.

- Collaborate with Cybersecurity, SOC, Data Engineering, Data Science and Cloud Engineering teams.

📌 Data Engineer - Databricks (Remote) (India)
🏢 HireFlex
📍 India