WHAT DOES A BIG DATA DO?

• Data Strategy: Drive the big data strategy and roadmap focusing on data provisioning, a strong data management vision, and optimization of data assets.
• Pipeline Analysis: Analyze big data pipeline implementation at the pattern and code level, identify issues, and provide remedial recommendations.
• ETL Support: Support ETL pipeline investigations to ensure data pipelines are working as per design.
• Cluster Monitoring: Analyze cluster performance and investigate individual job impact on meeting daily SLAs with various business lines.
• Flow Design: Design information flow for new reporting requirements and build data architecture.
• Pipeline Development: Develop data pipelines to support reporting products.
• Data Analysis: Support data analysis for reporting systems and downstream users of the Consumer Zone.
• Disaster Recovery: Support the new design and implementation of a data lake disaster recovery system.
• Solution Architecture: Render, own, and drive the solution architecture for Corporate Security and Future of Work domains.

In complex enterprise environments, a detailed Big Data Job Description defines duties that ensure reliable pipelines, system performance, and scalable architecture solutions.

• Architecture Design: Define an end-to-end architecture design solution.
• Estimate Preparation: Prepare high-level and detailed estimates.
• Technology Adoption: Understand new technology trends, new tools, and implement POC.
• DevOps Pipeline: Design and build a DevOps pipeline for large-scale implementation of data pipelines for both analytical and operational data applications.
• Platform Enablement: Build capabilities on the platform that enable data analysts to rapidly consume data pipelines through data applications and exploration capabilities.
• Model Management: Define and update data models and associated technical and business metadata.
• Team Collaboration: Work closely with Product Owner/s, Architects, and delivery teams to build systems that drive clients towards its strategic platform vision.
• Framework Optimization: Optimize and contribute to existing platform frameworks, components, and templates enabling future development efficiencies.
• Knowledge Sharing: Knowledge transfer throughout the organization via participation in workshops, appropriate documentation, and internal presentations establishing thought leadership and capability excellence on client’s platform.

• Threat Intelligence: Create timely and actionable threat intelligence, including IOCs, TTPs, and valuable insights.
• Customer Protection: Proactively protect customers by blocking attacks and providing contextual threat information.
• Pipeline Engineering: Build efficient data pipelines for collecting, processing, and analyzing large volumes of threat data.
• Backend Development: Design, develop, and monitor data pipelines in a senior back-end development role.
• API Creation: Create reliable and robust REST web service APIs for front-end web applications.
• Team Collaboration: Collaborate with the threat analysis and data modeling team.
• Data Flow: Ensure the timely and efficient flow of threat-related data.
• Cyber Defense: Support the mission of safeguarding customers from cyber threats through data-driven solutions.

To highlight expertise in secure data systems, a strong Big Data Resume demonstrates experience in pipeline engineering and cyber defense responsibilities.

• Innovation Development: Contributes to the development of innovative principles, ideas, and practices.
• Project Leadership: Leads large, cross-functional activities or projects that affect the organization's long-term goals and objectives.
• Strategy Development: Develops strategy and functionality to align with the company's business initiatives.
• Business Adaptability: Work in different business environments.
• Executive Interaction: Interacts with high-level Individual Contributors, C-Level Managers, Directors, Executives, and Core Teams.
• Project Management: Leads multiple and the most complex projects requiring software applications development.
• Design Review: Reviews and evaluates designs and project activities for compliance with development guidelines and standards.
• Quality Improvement: Provides tangible feedback to improve product quality and mitigate failure risk.
• Technology Evaluation: Identifies and evaluates new technologies, innovations, and outsourced development partner relationships for alignment with technology roadmap and business value.
• Architecture Planning: Creates plans for integration and updates into the architecture.

Build Your Best Big Data Resume Builder Today