Principal Engineer - Data Engineer

Staples India; Chennai District; On-site; INR 3,000,000 - 6,000,000; Full time

Job summary

Staples India Business Innovation Hub Private Limited in Chennai seeks a senior data architect to define and drive enterprise data strategy, owning architectures for data platforms, pipelines, and ecosystems. You will lead design across multi-cloud environments, aligning with business goals and ensuring scalability.

You will mentor engineers, set governance and observability, champion modern data stack (Snowflake, DBT, Airflow, Kafka, Spark), and collaborate with stakeholders to deliver trusted

Qualifications

• Bachelor's degree in CS/IS/Engineering or related field (Master’s preferred).
• 11–15 years of progressive experience in data engineering or related fields.
• Deep expertise in SQL, data warehousing, and large-scale data modeling.
• Minimum 5 years of experience with Snowflake or another modern cloud data warehouse at scale.
• Minimum 3 years of experience with Python or equivalent programming languages for ETL/ELT and automation.
• Proven experience architecting data platforms on major cloud providers (AWS, Azure, or GCP).
• Hands-on experience with orchestration tools (Airflow, ADF, Luigi, etc.) and DBT.
• Strong track record in designing and implementing large-scale data pipelines and solutions.
• Demonstrated experience leading cross-functional teams and mentoring senior engineers.
• Excellent communication skills for engaging with business stakeholders and cross-functional partners.

Responsibilities

• Define and drive enterprise data strategy and architecture aligned with business goals.
• Architect high-performance data solutions across multi-cloud environments (AWS, Azure, GCP).
• Establish governance, testing, observability, and security across data platforms.
• Mentor engineers and lead cross-functional data teams.
• Partner with analytics and product teams to deliver trusted, business-ready data.
• Champion modern data stack technologies (Snowflake, DBT, Airflow, Kafka, Spark).
• Design data warehouses, lakes, and real-time pipelines for scalability and availability.
• Ensure regulatory compliance and data privacy across platforms.
• Foster collaboration and knowledge sharing across teams.

Skills

Data architecture

Data governance

Leadership

Mentoring

Cross-functional collaboration

Communication

Cloud data platforms

SQL

ETL/ELT design

Education

Bachelor's degree in CS/IS/Engineering-related field

Master’s or equivalent advanced degree preferred

Tools

Snowflake

Airflow

DBT

Kafka

Spark

CI/CD

Job description

Staples India Business Innovation Hub Private Limited | Permanent

Define and Drive Enterprise Data Strategy

Develop and own the strategic architecture for enterprise-scale data platforms, pipelines, and ecosystems, ensuring alignment with business objectives and long-term scalability.

Architect High-Performance Data Solutions

Lead the design and implementation of robust, large-scale data solutions across multi-cloud environments (AWS, Azure, GCP), optimizing for performance, reliability, and cost efficiency.

Create and enforce best practices, coding standards, and architectural frameworks for data engineering teams, fostering a culture of quality, automation, and continuous improvement.

Provide Technical Leadership and Mentorship

Act as a trusted advisor and mentor to engineers across multiple teams and levels, guiding technical decisions, career development, and knowledge sharing.

Align Data Strategy with Business Goals

Partner with senior business and technology stakeholders to translate organizational objectives into actionable data strategies, ensuring measurable business impact.

Champion Modern Data Stack Adoption

Drive the adoption and integration of cutting-edge technologies such as Snowflake, DBT, Airflow, Kafka, Spark, and other orchestration and streaming tools to modernize data infrastructure.

Architect and Optimize Data Ecosystems

Design and manage enterprise-grade data warehouses, data lakes, and real-time streaming pipelines, ensuring scalability, security, and high availability.

Implement Enterprise Testing and Observability

Establish rigorous testing, validation, monitoring, and observability frameworks to guarantee data integrity, reliability, and compliance across all environments.

Ensure Governance and Compliance

Oversee data governance initiatives, including lineage tracking, security protocols, regulatory compliance, and privacy standards across platforms.

Enable Cross-Functional Collaboration

Work closely with analytics, data science, and product teams to deliver trusted, business-ready data that accelerates insights and decision-making.

Provide Thought Leadership

Stay ahead of emerging technologies and industry trends, influencing enterprise data strategy and advocating for innovative solutions that drive competitive advantage.

Oversee large-scale data platform deployments, ensuring operational excellence, scalability, and cost optimization for global business needs.

Requirements

Basic Qualifications

• Bachelor’s degree in Computer Science, Information Systems, Engineering, or a related field (Master’s or equivalent advanced degree preferred)
• 11–15 years of progressive experience in data engineering or related fields
• Deep expertise in SQL, data warehousing, and large-scale data modeling
• Minimum 5 years of experience with Snowflake or another modern cloud data warehouse at scale
• Minimum 3 years of experience with Python or equivalent programming languages for ETL/ELT and automation
• Proven experience architecting data platforms on major cloud providers (AWS, Azure, or GCP)
• Hands-on experience with orchestration tools (Airflow, ADF, Luigi, etc.) and data transformation frameworks (DBT)
• Strong track record in designing and implementing large-scale data pipelines and solutions
• Demonstrated experience leading cross-functional teams and mentoring senior engineers
• Excellent communication skills for engaging with business stakeholders and cross-functional partners

Preferred Qualifications

• Expertise in Real-Time Data Processing
• Hands-on experience with streaming platforms such as Apache Kafka, Spark Streaming, and Apache Flink, enabling low-latency, high-throughput data pipelines for real-time analytics.
• Strong DevOps and CI/CD Practices
• Deep understanding of DevOps principles, automated CI/CD pipelines, and Git-based workflows tailored for data engineering environments, ensuring rapid, reliable deployments.
• Domain Knowledge in Retail and E-Commerce
• Proven experience working with customer-centric data ecosystems, leveraging data to drive personalization, operational efficiency, and business growth in retail or e-commerce contexts.
• Track Record of Driving Innovation
• Recognized for introducing technical innovations, improving engineering processes, and advancing organizational data maturity through strategic initiatives.
• Experience in ML Ops and AI/ML Lifecycle
• Practical knowledge of ML Ops frameworks, including building data pipelines for model training, managing feature stores, and implementing monitoring solutions for AI/ML models in production.
• Strategic Alignment and Leadership
• Ability to understand and interpret organizational vision and decision-making frameworks, aligning team objectives and personal goals to deliver measurable business impact.
• Technology Evangelism and Trend Awareness
• Up-to-date with emerging technologies, industry best practices, and modern data architectures; consistently brings innovative ideas and thought leadership to the team.