Data Architect (Strategic) @ Robert Bosch

Key Responsibilities

1. Data Architecture Design
   • Define and design Big Data architecture solutions, including data lakes, data warehouses, and real-time processing systems.
   • Architect and implement scalable, secure, and high-performance data pipelines and data integration solutions.
   • Ensure alignment with industry best practices and organizational goals for data architecture.
2. Big Data Ecosystem Management
   • Develop and manage workflows using Big Data tools like Hadoop, Spark, Kafka, Hive, and Flink.
   • Leverage cloud-based Big Data services (AWS EMR, Azure Synapse, GCP BigQuery, or similar) to optimize performance and scalability.
   • Oversee the implementation of streaming data platforms to support real-time analytics.
3. Data Modeling and Integration
   • Design and maintain data models (conceptual, logical, and physical) that support structured and unstructured data.
   • Build robust ETL/ELT processes to ingest, process, and integrate large volumes of diverse data sources.
   • Implement APIs and frameworks for seamless data sharing and consumption.
4. Data Governance and Security
   • Establish frameworks to ensure data quality , lineage, and governance across the data lifecycle.
   • Implement security measures for data at rest and in motion using encryption and access controls.
   • Ensure compliance with global data regulations such as GDPR, CCPA, or similar.
5. Gen AI exposure / experience as mandatory .
6. Collaboration and Stakeholder Engagement
   • Partner with data engineers, data scientists, business analysts, and IT teams to align architecture with business needs.
   • Translate complex technical concepts into actionable insights for stakeholders.
7. Performance Optimization and Monitoring
   • Monitor and optimize performance of Big Data systems, ensuring low latency and high reliability.
   • Troubleshoot and resolve performance bottlenecks in distributed data environments.
8. Emerging Technology and Innovation
   • Evaluate and implement emerging technologies, such as Graph Databases, NoSQL Systems, and AI-driven analytics platforms .
   • Continuously explore innovations in the Big Data ecosystem to drive efficiency and competitive advantage.

Success Criteria

• Explore different tech stacks and architecture design
• Document supporting evidence with KPIs for decision on solution design and document product guideline and protocols to seamlessly utilize the framework
• Prior experience with ETL & Big Data to set up scalable pipeline to process data in real time and batch
• Develop configurable solutions to support cross functional requirements and support multiple platforms.
• Experience in managing cross-functional team, requirements gathering , day-to-day relationships with clients, and stakeholders supporting clients to achieve better outcomes

Preferred Qualifications

• Experience :
  • 10+ years of experience in data architecture, with at least 3+ years focusing on Big Data technologies.
  • 5+ years as Data Architect with proficiency working in environments supporting solutions design
  • Proven track record of delivering end-to-end Big Data solutions in enterprise environments.
• Technical Expertise :
  • Strong understanding of Big Data frameworks like Hadoop, Spark, Kafka, Hive, Flink, and Presto.
  • Proficiency in cloud-based Big Data platforms (AWS EMR, Azure Synapse, GCP BigQuery, or Databricks).
  • Expertise in database systems, including both SQL (e. g. , PostgreSQL, MySQL) and NoSQL (e. g. , MongoDB, Cassandra).
  • Hands-on experience with ETL tools like Talend, Informatica, or Apache NiFi.
  • Familiarity with data visualization tools (e. g. , Tableau, Power BI) and analytics platforms.

• Certifications :
  • Certifications such as AWS Certified Data Analytics, Azure Data Engineer Associate, GCP Professional Data Engineer, or Hadoop certifications are highly desirable.

Key Attributes

• Strong analytical and problem-solving skills with a passion for data-driven innovation.
• Excellent communication and collaboration abilities to engage both technical and non-technical stakeholders.
• Strategic mindset with a focus on scalability, performance, and alignment with business objectives.
• Ability to thrive in fast-paced environments and handle multiple priorities effectively.