Principal / Senior Data Engineer (Data Platform Architect)

As a Principal / Senior Data Engineer (Data Platform Architect) at our company, you will play a crucial role in designing and building large-scale, enterprise-grade data platforms from scratch. Your deep expertise in data architecture, distributed systems, scalability, governance, and performance engineering will be essential in leading platform-level decisions. **Key Responsibilities:** - Architect and design large-scale modern data platforms, encompassing batch and streaming data processing. - Define enterprise-level data architecture standards, governance models, and best practices for optimal performance. - Construct scalable, high-performance data lakes, lakehouses, and warehouse architectures. - Develop real-time streaming pipelines using technologies such as Kafka, Spark, and Flink. - Lead initiatives for technology selection, platform modernization, and optimization to ensure scalability and fault tolerance. - Implement CI/CD, observability, and data reliability frameworks for streamlined operations. - Drive data modeling strategies catering to analytics, ML, and reporting requirements. - Collaborate closely with business, analytics, ML, and DevOps teams to align data engineering efforts. - Mentor and guide junior data engineers to foster a collaborative and growth-oriented environment. **Required Technical Expertise:** - 8+ years of hands-on experience in Data Engineering with a track record of designing enterprise-scale data platforms. - Profound expertise in distributed systems and big data technologies. - Strong proficiency in Spark, Kafka, Data Warehousing (Snowflake, Redshift, BigQuery, Databricks), and Lakehouse architectures (Delta Lake, Iceberg, Hudi). - Extensive experience in cloud platforms such as AWS, Azure, and GCP. - Advanced skills in data modeling, performance tuning, cost optimization strategies, SQL, Python, and/or Scala. - Familiarity with CI/CD and Infrastructure as Code practices. **Architecture Expectations:** - Showcase experience in designing systems capable of handling data at TBPB scale. - Demonstrate expertise in multi-region, high-availability architecture, data governance, security implementation, platform reliability, and observability design. - Ability to define a roadmap and long-term data strategy to align with business objectives. In addition to technical skills, soft skills play a vital role in this role, including strong stakeholder communication, the ability to influence architectural decisions, strategic thinking with hands-on execution capability, and leadership and mentoring abilities. As a Principal / Senior Data Engineer (Data Platform Architect) at our company, you will play a crucial role in designing and building large-scale, enterprise-grade data platforms from scratch. Your deep expertise in data architecture, distributed systems, scalability, governance, and performance engineering will be essential in leading platform-level decisions. **Key Responsibilities:** - Architect and design large-scale modern data platforms, encompassing batch and streaming data processing. - Define enterprise-level data architecture standards, governance models, and best practices for optimal performance. - Construct scalable, high-performance data lakes, lakehouses, and warehouse architectures. - Develop real-time streaming pipelines using technologies such as Kafka, Spark, and Flink. - Lead initiatives for technology selection, platform modernization, and optimization to ensure scalability and fault tolerance. - Implement CI/CD, observability, and data reliability frameworks for streamlined operations. - Drive data modeling strategies catering to analytics, ML, and reporting requirements. - Collaborate closely with business, analytics, ML, and DevOps teams to align data engineering efforts. - Mentor and guide junior data engineers to foster a collaborative and growth-oriented environment. **Required Technical Expertise:** - 8+ years of hands-on experience in Data Engineering with a track record of designing enterprise-scale data platforms. - Profound expertise in distributed systems and big data technologies. - Strong proficiency in Spark, Kafka, Data Warehousing (Snowflake, Redshift, BigQuery, Databricks), and Lakehouse architectures (Delta Lake, Iceberg, Hudi). - Extensive experience in cloud platforms such as AWS, Azure, and GCP. - Advanced skills in data modeling, performance tuning, cost optimization strategies, SQL, Python, and/or Scala. - Familiarity with CI/CD and Infrastructure as Code practices. **Architecture Expectations:** - Showcase experience in designing systems capable of handling data at TBPB scale. - Demonstrate expertise in multi-region, high-availability architecture, data governance, security implementation, platform reliability, and observability design. - Ability to define a roadmap and long-term data strategy to align with business objectives. In addition to technical skills, soft skills play a vital role in this role, including strong