Principal Engineer - Data Engineering

We are seeking a Principal Staff Engineer – Data to serve as the most senior individual contributor within the data engineering organization. This role will define the long-term technical vision for Freshworks' data platform and drive architectural decisions across data ingestion, processing, storage, governance, analytics, and AI/ML enablement.

The ideal candidate has deep expertise in large-scale distributed data systems, real-time streaming architectures, cloud data platforms, and modern lakehouse technologies. They combine strong technical judgment with the ability to influence engineering strategy across multiple teams and business functions.

Key Responsibilities

Data Architecture & Strategy

• Define and own the long-term architecture vision and roadmap for Freshworks' enterprise data platform.

• Drive key technology decisions including platform selection, build-versus-buy evaluations, migrations, and deprecations.

• Establish architecture standards, engineering principles, and reference patterns that scale across teams.

• Evaluate emerging technologies and recommend strategic investments aligned with business goals.

Large-Scale Data Platform Engineering

• Architect and scale real-time and batch data platforms supporting high-volume, low-latency workloads.

• Design streaming architectures for event ingestion, CDC, and real-time processing using technologies such as Kafka, Kinesis, or Pub/Sub.

• Lead the design of Spark-based distributed processing systems for large-scale data workloads.

• Architect performant and cost-efficient data warehouse and serving layers using Snowflake and cloud-native platforms.

• Drive lakehouse initiatives leveraging technologies such as Iceberg, Delta Lake, Databricks, and cloud-native services.

• Establish best practices for platform reliability, observability, scalability, performance, and cost optimization.

Analytics, Data Products & AI Enablement

• Define reusable data models, semantic layers, and curated data products that support self-service analytics.

• Partner with product, analytics, and business teams to translate complex requirements into scalable platform capabilities.

• Build foundational data capabilities that accelerate AI/ML and GenAI initiatives.

• Enable trusted, discoverable, and reusable datasets across the organization.

Governance, Security & Quality

• Define enterprise-wide standards for data governance, metadata management, lineage, cataloging, and stewardship.

• Establish data quality frameworks, monitoring standards, and reliability metrics.

• Ensure compliance with security, privacy, and regulatory requirements.

• Promote a culture of trusted and well-governed data across the organization.

Technical Leadership

• Serve as the highest technical authority for data architecture and platform design decisions.

• Lead architecture reviews and provide guidance on complex technical challenges across multiple teams.

• Mentor Staff and Senior engineers and help elevate engineering standards across the organization.

• Influence engineering strategy, platform investments, and long-term technical direction.

• Drive alignment among engineering, product, analytics, and leadership stakeholders.

Required Qualifications

• Bachelor's or Master's degree in Computer Science, Engineering, Information Systems, or a related discipline.

• 15+ years of experience in Data Engineering, Data Platform Engineering, or Data Architecture.

• Proven experience designing and operating large-scale, real-time data platforms in production environments.

• Deep hands-on expertise with Snowflake, Apache Spark, and modern cloud data platforms.

• Strong understanding of distributed systems, streaming architectures, data modeling, and data integration patterns.

• Experience designing enterprise-scale data platforms that support analytics, reporting, and AI/ML workloads.

• Demonstrated success leading cross-functional architecture initiatives in SaaS or product organizations.

• Proven ability to influence technical strategy and mentor senior engineering talent.

Preferred Qualifications

• Experience with lakehouse technologies such as Delta Lake, Apache Iceberg, and Databricks.

• Experience building data platforms supporting AI/ML, GenAI, feature stores, or training-data pipelines.

• Experience with enterprise data governance, metadata management, cataloging, lineage, and observability platforms.

• Experience driving platform cost optimization and FinOps initiatives for large-scale data environments.

• Track record of defining technical direction and delivering organization-wide platform transformations.

At Freshworks, we have fostered an environment that enables everyone to find their true potential, purpose, and passion, welcoming colleagues of all backgrounds, genders, sexual orientations, religions, and ethnicities. We are committed to providing equal opportunity and believe that diversity in the workplace creates a more vibrant, richer environment that boosts the goals of our employees, communities, and business. Fresh vision. Real impact. Come build it with us.