PRINCIPAL DATA ENGINEER - PATTERN
Posted on: December 28, 2025 | On-Site (Pune, India)
Company Name: Pattern.com | Reports To: Engineering Leadership
Division: Pattern Corporate-Engineering
Location: Pune, India | Employment Type: Full-Time
Schedule: On-Site (Office-Centric) | Experience Level: 08+ Years
ABOUT PATTERN
Are you obsessed with data, partner success, taking action, and changing the game? If you have a whole lot of hustle and a touch of nerd, come work with Pattern! We want you to use your skills to push one of the fastest-growing companies headquartered in the US to the top of the list.
Pattern accelerates brands on global eCommerce marketplaces leveraging proprietary technology and artificial intelligence. Utilizing more than 46 trillion data points, sophisticated machine learning and AI models, Pattern optimizes and automates all levers of eCommerce growth for global brands, including advertising, content management, logistics and fulfillment, pricing, forecasting, and customer service.
Hundreds of global brands depend on Pattern's eCommerce acceleration platform every day to drive profitable revenue growth across 60+ global marketplaces—including Amazon, Walmart.com, Target.com, eBay, Tmall, TikTok Shop, JD, and Mercado Libre. To learn more, visit pattern.com or email press@pattern.com.
Recognition & Awards
Pattern has been named one of the fastest-growing tech companies headquartered in North America by Deloitte and one of the best-led companies by Inc. We place employee experience at the center of our business model and have been recognized as one of Newsweek's Global Most Loved Workplaces®.
ROLE OVERVIEW
As a Principal Data Engineer at Pattern, you will lead the design, development, and optimization of enterprise-scale data pipelines and architectures to drive data-driven decision-making across our organization. This role requires a visionary technologist who can architect efficient data tables and schemas to enhance query performance while ensuring seamless integration with cross-functional teams.
You will be at the forefront of building and scaling data infrastructure that processes 46+ trillion data points, directly impacting how hundreds of global brands make critical business decisions. This position offers the unique opportunity to work with cutting-edge technologies including Apache Spark, AWS cloud platforms, Snowflake, and advanced AI/ML integration while mentoring the next generation of data engineers.
In this leadership role, you will not only design and implement technical solutions but also shape the strategic direction of Pattern's data infrastructure. You'll collaborate with data scientists, product managers, and engineering teams across the globe to build systems that power real-time analytics, machine learning models, and business intelligence tools that drive Pattern's continued growth and success.
KEY RESPONSIBILITIES
Data Pipeline Development & Optimization
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Design and implement high-performance data pipelines using ETL processes, batch and streaming frameworks such as Apache Spark and Apache Airflow, ensuring robust data flow across the organization
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Architect and deploy cloud-based solutions on AWS platforms, leveraging services like S3, EMR, Redshift, Lambda, and Glue to create scalable data infrastructure that can handle massive data volumes
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Optimize data ingestion, transformation, and storage workflows to meet stringent scalability, reliability, and latency requirements that support real-time decision-making across Pattern's global operations
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Implement comprehensive monitoring and alerting systems to ensure pipeline reliability, data quality, and performance optimization across all data workflows, minimizing downtime and data inconsistencies
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Build automated testing frameworks to validate data accuracy, pipeline integrity, and transformation logic throughout the data lifecycle, ensuring data trustworthiness
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Design fault-tolerant and resilient data systems that can recover gracefully from failures and maintain data consistency across distributed systems
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Establish data pipeline documentation and operational runbooks to ensure knowledge transfer and support operational excellence across the engineering team
Data Architecture & Query Efficiency
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Architect comprehensive database schemas and dimensional models including star and snowflake schemas to maximize query performance and reduce latency across analytical workloads processing trillions of data points
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Implement advanced indexing strategies, partitioning techniques, clustering keys, and materialized views to optimize data retrieval and enable faster analytics for business users and data scientists
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Design and maintain data lakes and data warehouses that support both structured and unstructured data, ensuring efficient storage patterns, cost optimization, and scalable retrieval mechanisms
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Establish best practices for data modeling that balance normalization with performance requirements, creating comprehensive documentation and standards for the engineering team to follow
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Conduct performance tuning and optimization of complex SQL queries, analyzing execution plans, reducing execution times, and minimizing resource consumption across the data platform
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Implement data compression and encoding strategies to optimize storage costs while maintaining query performance across large-scale datasets
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Design data retention and archival policies that balance accessibility needs with cost efficiency and regulatory compliance requirements
Collaboration & Data Governance
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Partner closely with data scientists, product managers, and engineers to align data infrastructure with evolving business needs, strategic objectives, and emerging use cases across Pattern's diverse business lines
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Establish comprehensive data governance frameworks, ensuring strict compliance with security standards, privacy regulations (including GDPR, CCPA, and other international data protection laws), and data quality benchmarks
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Mentor and guide junior and mid-level engineers, fostering best practices in data engineering, code quality, architectural decision-making, and professional development
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Lead architecture review sessions to evaluate technical approaches, identify potential issues, ensure alignment with enterprise standards, and promote knowledge sharing across teams
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Create and maintain technical documentation including architecture diagrams, data flow documentation, API specifications, and operational runbooks that enable team scalability
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Implement data lineage and metadata management solutions to improve data discoverability, understanding, and trust across the organization, enabling self-service analytics
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Champion data quality initiatives by implementing validation frameworks, defining data quality metrics, and establishing processes for continuous monitoring and improvement
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Facilitate cross-functional collaboration between engineering, analytics, product, and business teams to ensure data solutions meet diverse stakeholder requirements
Innovation & Technical Leadership
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Stay ahead of industry trends including AI/ML integration, real-time analytics, data mesh architectures, and emerging data technologies, advocating for their strategic adoption when they deliver business value
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Lead technical strategy for data infrastructure, carefully balancing innovation with operational stability, business continuity, and total cost of ownership considerations
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Drive proof-of-concept initiatives for new technologies and methodologies, evaluating their potential impact on Pattern's data ecosystem through rigorous testing and analysis
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Participate in technical planning and roadmap development, providing expert guidance on data infrastructure capabilities, limitations, and strategic investments needed for future growth
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Champion engineering excellence through comprehensive code reviews, architectural discussions, technical presentations, and knowledge-sharing sessions that elevate the entire team
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Represent Pattern's data engineering function at internal forums and potentially external conferences, sharing insights and learning from the broader data engineering community
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Evaluate and recommend tools, platforms, and vendors that can enhance Pattern's data capabilities while ensuring they align with security, compliance, and architectural standards
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Foster a culture of experimentation and continuous improvement, encouraging team members to explore new approaches and learn from both successes and failures
REQUIRED QUALIFICATIONS
Technical Expertise
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8+ years of progressive experience in data engineering, with demonstrated focus on ETL processes, data modeling, and cloud-based architectures at scale
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Advanced proficiency in SQL with proven ability to write complex queries involving multiple joins, window functions, CTEs, and query optimization techniques for performance tuning
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Expert-level Python programming skills for data processing, automation, API development, and integration with various data tools and frameworks
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Hands-on experience with Apache Spark for large-scale data processing, including both batch and streaming applications, with understanding of Spark internals and optimization techniques
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Practical knowledge of Snowflake or similar cloud data warehouse platforms (such as Redshift, BigQuery), including optimization techniques, cost management, and best practices
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Deep understanding of database design principles, dimensional modeling techniques (Kimball methodology), normalization/denormalization strategies, and query optimization
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Extensive experience with AWS cloud services including EC2, S3, EMR, Redshift, Lambda, Glue, Kinesis, and related data engineering tools and services
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Strong familiarity with workflow orchestration tools such as Apache Airflow, Luigi, Prefect, or similar platforms for managing complex data pipelines
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Proficiency with version control systems (Git) and collaborative development practices including branching strategies, code reviews, and CI/CD integration
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Understanding of data security and encryption including data-at-rest and data-in-transit encryption, key management, and access control mechanisms
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Experience with data serialization formats such as Parquet, Avro, ORC, and understanding of when to use each format for optimal performance
Leadership & Collaboration
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Proven ability to lead technical teams, mentor engineers at various experience levels, and drive complex technical initiatives from conception to successful completion
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Demonstrated experience translating business requirements into scalable, efficient technical solutions that deliver measurable business value and align with organizational objectives
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Strong communication skills with ability to explain complex technical concepts to both technical and non-technical stakeholders, including executives and business users
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Track record of successful cross-functional collaboration with product, analytics, business intelligence, and operations teams in delivering data solutions
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Experience making architectural decisions that consider trade-offs between performance, cost, maintainability, and time-to-market, and providing technical guidance that aligns with organizational goals
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Ability to influence without direct authority, building consensus across teams and driving adoption of best practices and technical standards
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Strong problem-solving skills with ability to break down complex challenges into manageable components and develop pragmatic solutions
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Experience managing stakeholder expectations and communicating project status, risks, and technical constraints effectively
PREFERRED QUALIFICATIONS
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Expertise in machine learning model deployment and productionization, including experience with MLOps practices, model versioning, feature stores, and frameworks like MLflow or Kubeflow
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Hands-on experience with real-time analytics platforms such as Apache Kafka, AWS Kinesis, Apache Flink, or similar streaming technologies for processing high-velocity data
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Familiarity with DevOps practices including CI/CD pipelines, containerization (Docker), orchestration platforms (Kubernetes), and automated deployment strategies
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Experience with Infrastructure as Code tools like Terraform, CloudFormation, Ansible, or similar technologies for managing data infrastructure programmatically
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Knowledge of data visualization and BI tools such as Tableau, Looker, Power BI, or QuickSight for creating actionable insights and self-service analytics
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Background in eCommerce, retail, or marketplace analytics, understanding the unique data challenges including inventory management, pricing optimization, and customer behavior analysis
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Experience with NoSQL databases such as DynamoDB, MongoDB, Cassandra, or similar technologies for specific use cases
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Professional certifications in AWS (Solutions Architect, Data Analytics), Snowflake (SnowPro Core), or other relevant platforms demonstrating technical expertise
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Contributions to open-source projects or active participation in data engineering communities
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Experience with data quality frameworks such as Great Expectations, Deequ, or similar tools for automated data validation
OUR CORE VALUES
At Pattern, our core values define who we are and how we work. We seek team members who embody these principles in their daily work and interactions:
Game Changers
A game changer is someone who looks at problems with an open mind and shares new ideas with team members, regularly reassesses existing plans and attaches realistic timelines to goals, makes profitable, productive, and innovative contributions, and actively pursues improvements to Pattern's processes and outcomes. We value individuals who challenge the status quo constructively and drive meaningful change that benefits our partners and organization.
Data Fanatics
A data fanatic is someone who recognizes problems and seeks to understand them through data, draws unbiased conclusions based on data that lead to actionable solutions, and continues to track the effects of solutions using data. In this role, being a data fanatic means not just building data systems, but being passionate about how data drives decisions and continuously improving data quality, accessibility, and insights.
Partner Obsessed
An individual who is partner obsessed clearly explains the status of projects to partners and relies on constructive feedback, actively listens to partner expectations and delivers results that exceed them, prioritizes the needs of partners, and takes the time to create a personable experience for those interacting with Pattern. As a Principal Data Engineer, this means understanding how your technical decisions impact both internal stakeholders and the global brands we serve.
Team of Doers
Someone who is a part of a team of doers uplifts team members and recognizes their specific contributions, takes initiative to help in any circumstance, actively contributes to supporting improvements, and holds themselves accountable to the team as well as to partners. We value individuals who don't just identify problems but roll up their sleeves to solve them, while supporting and empowering their teammates.
WHAT YOU'LL GAIN AT PATTERN
Impact at Scale
- Work with cutting-edge technology processing 46+ trillion data points across global eCommerce platforms
- Support hundreds of global brands including Fortune 500 companies in their data-driven decision-making
- Build systems that directly impact millions of transactions and billions of dollars in eCommerce revenue
- See the tangible results of your work through improved business outcomes and partner success
Professional Growth
- Career advancement opportunities in a fast-growing tech company recognized by Deloitte as one of the fastest-growing companies in North America
- Technical leadership role with the ability to mentor engineers, shape data architecture strategy, and influence company-wide technical decisions
- Continuous learning environment with access to cutting-edge technologies, training resources, and opportunities to attend industry conferences
- Cross-functional exposure working with data science, product, engineering, and business teams across diverse domains
Culture & Environment
- Join a collaborative environment recognized as one of Newsweek's Global Most Loved Workplaces®
- Work in an innovation-driven culture that encourages experimentation, learning from failures, and adoption of emerging technologies
- Be part of a diverse and inclusive team that celebrates different perspectives and backgrounds
- Experience employee-centric policies that prioritize work-life balance, professional development, and overall wellbeing
Technical Excellence
- Exposure to diverse challenges across multiple global marketplaces including Amazon, Walmart, Target, eBay, and international platforms
- Opportunity to work with modern data stack including Spark, Airflow, Snowflake, AWS, and emerging AI/ML technologies
- Solve complex problems at the intersection of big data, machine learning, and real-time analytics
- Influence technical direction and contribute to architectural decisions that shape Pattern's data future
LOCATION & WORK ENVIRONMENT
This is a full-time, on-site position based in Pune, India. You will work from Pattern's office environment, collaborating closely with engineering teams, data scientists, and cross-functional partners both locally and globally. The role requires regular working hours with flexibility as needed to support global operations and collaborate with international teams across different time zones.
Pattern's Pune office provides a modern, collaborative workspace equipped with the tools and technology needed to excel in this role. You'll have access to high-performance computing resources, collaboration tools, and a supportive environment designed to foster innovation and productivity.
DIVERSITY & INCLUSION
Pattern is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. We believe that diverse perspectives, backgrounds, and experiences drive innovation and make us stronger as a company. We do not discriminate based on race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.
We encourage applications from candidates of all backgrounds and are committed to providing reasonable accommodations to individuals with disabilities throughout our hiring process and employment.
AI IN OUR HIRING PROCESS
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans, considering the full context of each candidate's qualifications, experience, and potential fit with our team and culture. If you would like more information about how your data is processed during the hiring process, please contact us.
HOW TO APPLY
If you're ready to take your data engineering career to the next level and make a significant impact at one of North America's fastest-growing tech companies, we want to hear from you. This is more than just a job—it's an opportunity to shape the future of eCommerce through data-driven innovation, work with cutting-edge technologies, and be part of a team that values your contributions and supports your growth.
To apply for this position:
- Submit your updated resume highlighting your relevant data engineering experience
- Include a cover letter explaining why you're excited about this opportunity and how your experience aligns with Pattern's needs
- Provide any relevant portfolio materials, GitHub profiles, or examples of your work (optional but encouraged)
- Be prepared to discuss your technical experience, leadership approach, and problem-solving methodology in interviews
Application Process Timeline:
- Application review: 1-2 weeks
- Initial screening call: 30 minutes
- Technical interviews: 2-3 rounds (including coding, system design, and architectural discussions)
- Final interviews: Leadership and culture fit discussions
- Offer and onboarding
We review applications on a rolling basis and encourage you to apply early. All applications are reviewed by our recruiting team, and we strive to provide timely feedback throughout the process.
CONTACT INFORMATION
Join Pattern and help us transform how global brands succeed in the digital economy. Your expertise in data engineering can make a real difference—apply today!
Pattern | Accelerating Global eCommerce Through Data-Driven Innovation
This job description is effective as of December 2024 and may be updated to reflect evolving business needs and opportunities.
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