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Job Description

Description :

Data Architecture & Design :

- Design and implement scalable, fault-tolerant, and high-performance data architectures supporting batch and streaming workloads.

- Define end-to-end data pipelines and platform architecture for large-scale data ingestion, processing, and consumption.

- Ensure architectural alignment with enterprise standards, cloud best practices, and long-term scalability goals.

Data Modeling & Integration :

- Design and maintain efficient data models (conceptual, logical, and physical) for analytics and operational use cases.

- Integrate data from multiple structured and unstructured sources, including databases, APIs, files, and event streams.

- Optimize data transformations and storage for performance, cost, and usability.

Big Data Technologies :

- Build and manage data processing solutions using big data frameworks and platforms (e.g., Spark, Hadoop, Kafka, Flink).

- Develop batch and real-time data pipelines using distributed computing technologies.

- Work with cloud-based big data services (AWS, Azure, or GCP) for ingestion, processing, and analytics.

Data Security & Governance :

- Implement data security, privacy, and access control mechanisms across the data ecosystem.

- Ensure compliance with regulatory requirements and internal governance policies.

- Define and enforce data quality, lineage, metadata management, and retention standards.

Collaboration & Stakeholder Management :

- Collaborate closely with data scientists, data engineers, analysts, and business stakeholders to deliver fit-for-purpose data solutions.

- Translate business requirements into technical designs and data architecture blueprints.

- Provide technical guidance, best practices, and recommendations to project teams and leadership.

Operational Excellence & Optimization :

- Monitor, troubleshoot, and optimize data pipelines for reliability and performance.

- Identify opportunities to improve system efficiency, reduce costs, and enhance data availability.

- Document architectures, data flows, and operational processes


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