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.

Qualifications :

Required Qualifications

• Bachelors or Masters 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.

Additional Information :

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.

Remote Work :

No

Employment Type :

Full-time