Principal Engineer - Data Engineering

As the Principal Staff Engineer Data at Freshworks, you will play a pivotal role in defining the long-term technical vision for Freshworks' data platform. Your strategic leadership will involve making architectural decisions across data ingestion, processing, storage, governance, analytics, and AI/ML enablement to drive global enterprise scale. Key Responsibilities: - Architect the Future Platform: Define and own the multi-year architectural vision and roadmap aligning engineering capabilities with core business goals. - Scale Global Data Ingestion: Design and optimize real-time streaming and high-volume batch data platforms for processing workloads with ultra-low latency. - Accelerate AI/ML & GenAI Initiatives: Develop high-fidelity data capabilities and pipelines to support predictive AI and Generative AI frameworks. - Establish Universal Data Trust: Introduce data governance, quality, and lineage standardizations to turn raw information into secure, discoverable, and reusable corporate data products. - Act as the Ultimate Technical Authority: Mentor Staff and Senior engineers while driving alignment across engineering, product, and executive stakeholders. Qualifications: - Skills Required: - Masterful understanding of distributed computing principles, cloud-native integration patterns, and massive-scale multi-tenant data platform design. - Deep expertise in Snowflake, Apache Spark, and cloud data ecosystems (AWS, GCP, or Azure). - Proficiency in real-time ingestion mechanics (Kafka, Kinesis, CDC) and lakehouse technologies (Iceberg, Delta Lake, Databricks). - Advanced competency in database schema design, semantic layer configuration, and data virtualization patterns. - Proven capability to optimize compute costs and implement advanced infrastructure monitoring and lineage tracing solutions. - Elite communication, presentation, and negotiation skills to translate technical realities into clear business strategies. - Professional Timeline: 15+ years of progressive experience in Data Engineering, Data Platform Engineering, or Data Architecture. - Transformation Track Record: Demonstrated success in designing and operating large-scale data environments and delivering platform transformations. - Industry Domain: Experience leading architecture initiatives within SaaS, cloud-native, or fast-paced product engineering organizations. - Talent Leadership: Track record of driving technical strategy and mentoring engineering talent. - Education: Bachelor's or Master's degree in Computer Science, Engineering, Information Systems, or related quantitative discipline. Freshworks fosters an inclusive environment where diversity is embraced, enabling individuals to reach their full potential. They are committed to equal opportunity and believe that a diverse workplace enhances employee goals and business outcomes. Join Freshworks to be a part of a forward-thinking team making a real impact. As the Principal Staff Engineer Data at Freshworks, you will play a pivotal role in defining the long-term technical vision for Freshworks' data platform. Your strategic leadership will involve making architectural decisions across data ingestion, processing, storage, governance, analytics, and AI/ML enablement to drive global enterprise scale. Key Responsibilities: - Architect the Future Platform: Define and own the multi-year architectural vision and roadmap aligning engineering capabilities with core business goals. - Scale Global Data Ingestion: Design and optimize real-time streaming and high-volume batch data platforms for processing workloads with ultra-low latency. - Accelerate AI/ML & GenAI Initiatives: Develop high-fidelity data capabilities and pipelines to support predictive AI and Generative AI frameworks. - Establish Universal Data Trust: Introduce data governance, quality, and lineage standardizations to turn raw information into secure, discoverable, and reusable corporate data products. - Act as the Ultimate Technical Authority: Mentor Staff and Senior engineers while driving alignment across engineering, product, and executive stakeholders. Qualifications: - Skills Required: - Masterful understanding of distributed computing principles, cloud-native integration patterns, and massive-scale multi-tenant data platform design. - Deep expertise in Snowflake, Apache Spark, and cloud data ecosystems (AWS, GCP, or Azure). - Proficiency in real-time ingestion mechanics (Kafka, Kinesis, CDC) and lakehouse technologies (Iceberg, Delta Lake, Databricks). - Advanced competency in database schema design, semantic layer configuration, and data virtualization patterns. - Proven capability to optimize compute costs and implement advanced infrastructure monitoring and lineage tracing solutions. - Elite communication, presentation, and negotiation skills to translate technical realities into clear business strategies.