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Principal Engineer

COVESTIC2

Hyderabad, IN1d ago
Seniority
Staff

About the role

We are seeking an accomplished and visionary Principal Engineer (Individual Contributor) to drive the technical strategy, architecture, and delivery of next-generation data platforms and analytics solutions. This role operates as a senior hands-on technical leader working across globally distributed teams in India, the United Kingdom, and the United States.

Reporting to the Director of Data Engineering and Analytics, this role is responsible for defining enterprise data platform direction, ensuring architectural excellence, and leading complex technical initiatives from design through execution. You will partner closely with leaders across Product, Enterprise Architecture, Analytics, Security, Risk, Compliance, and Operations to align data engineering solutions with business priorities and regulatory requirements.

Key Responsibilities:

Technical & Architectural Leadership

· Serve as a senior technical authority for data engineering and data platform architecture across the enterprise.

· Own the design and implementation of complex, large-scale data platforms and pipelines.

· Lead by example through hands-on architecture, design reviews, technical problem solving, and selective coding.

Data Platform Strategy

· Translate business and analytical objectives into a clear, actionable data engineering and platform strategy.

· Define and influence the technical roadmap for cloud-native data platforms leveraging AWS, Azure, Snowflake, Databricks, and emerging technologies.

· Drive alignment to enterprise data architecture standards and best practices.

Architectural Excellence

· Provide architectural governance and technical leadership across:

· AWS (S3, Iceberg, Glue, Lambda, Lake Formation, EMR, Redshift)

· Modern ELT/ETL frameworks (dbt, Airflow)

· Azure Data Factory

· Snowflake and Databricks ecosystems

· Ensure platforms are secure, scalable, cost-efficient, and resilient.

Platform Engineering & Delivery

· Lead the design, build, and optimization of batch and real-time data pipelines supporting analytics, regulatory reporting, payments processing, and real-time decisioning.

· Ensure high availability, performance, reliability, and observability across global data environments.

· Act as an escalation point for complex technical and production issues.

Engineering Excellence & Data Ops

· Champion engineering rigor through Data Ops, automation, CI/CD for data workloads, metadata management, and observability.

· Drive improvements in data quality, reliability, delivery consistency, and operational maturity.

· Establish reusable patterns, frameworks, and standards to accelerate delivery.

Cross-Regional Collaboration

· Work closely with globally distributed engineering teams to ensure consistent technical standards and platform practices.

· Provide technical mentorship and guidance without direct people management responsibility.

· Foster strong collaboration across regions and functions.

Partner & Influence

· Build strong partnerships with Product, Enterprise Architecture, Analytics, Security, Legal, Risk, Compliance, and Operations.

· Influence enterprise-level technical decisions through expertise and thought leadership.

· Represent data engineering in architecture reviews and strategic initiatives.

Metrics & Continuous Improvement

· Define and track technical KPIs related to data quality, platform reliability, performance, and cost efficiency.

· Use data-driven insights to continuously improve platform outcomes.

Strategic Communication

· Clearly communicate platform strategy, architecture decisions, risks, and progress to senior leadership.

· Serve as a trusted advisor on data platform modernization and transformation initiatives.

Technology Evolution

· Lead modernization efforts including cloud migration, adoption of open table formats (e.g., Iceberg), and data democratization for analytics and machine learning.

· Ensure platforms meet evolving requirements for global payments, compliance, and real-time intelligence.

 

Qualifications

· 12+ years of experience in data engineering, data architecture, or platform engineering.

· Demonstrated success operating at a Principal-level individual contributor capacity on enterprise-scale platforms.

· Bachelor’s degree in computer science, Engineering, Information Systems, or a related technical field.

Technical Expertise

· Deep hands-on experience with:

o AWS (S3, Glue, Lake Formation, EMR, Iceberg, Redshift, Lambda)

o Azure Data Factory

o Snowflake and Databricks

· Strong proficiency in Python, Spark, dbt, Airflow, and modern ELT/ETL frameworks.

· Extensive solution architecture experience governing complex, enterprise data ecosystems.

· Strong Agile delivery experience (Scrum, SAFe).

· Exceptional communication and influence skills with executive and senior technical stakeholders.

· Passion for building scalable, reliable, and high-quality data platforms.

Perks & benefits

  • Distributed Team

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