SENIOR DATA ENGINEER -PATTERN
Posted on: December 28, 2025 | On-Site (Pune, India)
Company Name: Pattern.com | Reports To: Data Engineering Management
Division: Pattern Corporate-Engineering
Location: Pune, India | Employment Type: Full-Time
Schedule: On-Site (Office-Centric) | Experience Level: 07+ 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.
Industry Recognition & Excellence
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®. Our commitment to innovation, data excellence, and employee satisfaction makes Pattern an exceptional place to advance your data engineering career.
ROLE OVERVIEW
Pattern values data and the engineering required to take full advantage of it. As a Senior Data Engineer at Pattern, you will be working on business problems that have a huge impact on how the company maintains our competitive edge. This is not just another data engineering role—it's an opportunity to shape how one of the fastest-growing eCommerce technology companies in North America leverages data to drive strategic decisions and deliver exceptional value to global brands.
In this senior-level position, you'll architect and build sophisticated data pipelines that process trillions of data points daily, enabling real-time analytics, machine learning models, and business intelligence that power Pattern's eCommerce acceleration platform. You'll work at the intersection of big data technologies, cloud computing, and business intelligence, creating solutions that directly impact revenue optimization, inventory forecasting, pricing strategies, and partner success across 60+ global marketplaces.
As a technical leader, you'll not only design and implement cutting-edge data solutions but also mentor junior data engineers, collaborate with cross-functional teams including data scientists and business analysts, and drive data quality initiatives that ensure Pattern maintains its competitive advantage through superior data engineering practices. Your expertise will be instrumental in scaling our data infrastructure to meet the exponential growth of our platform and partner base.
ESSENTIAL DUTIES AND RESPONSIBILITIES
Data Pipeline Development & Automation
Develop, deploy, and support automated, scalable real-time and batch data streams from a variety of sources into the lakehouse architecture. You'll build robust ETL/ELT pipelines that ingest data from multiple eCommerce marketplaces, internal systems, third-party APIs, and partner platforms, ensuring data flows seamlessly into our centralized data infrastructure.
Design and implement streaming data pipelines that process real-time events for immediate analytics and decision-making. You'll work with technologies like Apache Kafka, AWS Kinesis, or similar streaming platforms to enable real-time data processing for critical business functions such as inventory management, pricing optimization, and fraud detection.
Build batch processing workflows using Apache Spark, Apache Airflow, or similar orchestration tools to handle large-scale data transformations, aggregations, and enrichment processes. You'll optimize these workflows for performance, cost-efficiency, and reliability while ensuring they can scale to handle Pattern's massive data volumes.
Implement data pipeline orchestration and scheduling using tools like Apache Airflow, AWS Step Functions, or similar workflow management systems. You'll create dependencies, handle error scenarios, implement retry logic, and ensure data pipelines execute reliably according to business SLAs.
Data Quality & Governance
Develop and implement data auditing strategies and processes to ensure data quality across all data products and pipelines. You'll establish data validation frameworks, implement automated data quality checks, and create monitoring dashboards that provide visibility into data health metrics.
Identify and resolve problems associated with large-scale data processing workflows. You'll troubleshoot complex data issues, perform root cause analysis, implement preventive measures, and ensure data accuracy, completeness, and consistency across all data systems.
Implement technical solutions to maintain data pipeline processes and troubleshoot failures. You'll build robust error handling mechanisms, implement alerting systems, create runbooks for common failure scenarios, and ensure minimal downtime through proactive monitoring and rapid incident response.
Foster data expertise and own data quality for assigned areas of ownership. You'll become a subject matter expert for specific data domains, establish data quality standards, implement data governance policies, and ensure compliance with data privacy regulations and security requirements.
Drive data governance initiatives including data cataloging, metadata management, data lineage tracking, and access control. You'll work with stakeholders to establish data ownership, define data standards, and implement policies that ensure data is discoverable, trustworthy, and properly secured.
Collaboration & Technical Leadership
Collaborate with technology teams and partners to specify data requirements and provide access to data. You'll work closely with data scientists, analysts, product managers, and business stakeholders to understand their data needs, design appropriate data models, and deliver data products that enable self-service analytics and insights.
Translate business and analytics requirements for data to comprehensive data models and pipelines. You'll bridge the gap between business needs and technical implementation, designing dimensional models, fact tables, and data marts that support analytical use cases while maintaining performance and scalability.
Lead and mentor a team of Data Engineers, providing technical guidance, code reviews, architecture recommendations, and professional development support. You'll help junior engineers grow their skills, establish best practices, and create a culture of technical excellence within the data engineering team.
Work with data infrastructure teams to triage issues and drive to resolution. You'll collaborate with DevOps, cloud infrastructure, and platform engineering teams to optimize data platform performance, implement infrastructure improvements, and ensure the data ecosystem operates efficiently.
Performance Optimization & Innovation
Tune application and query performance using profiling tools and SQL or other relevant query languages. You'll analyze query execution plans, identify bottlenecks, implement indexing strategies, optimize data models, and leverage caching mechanisms to ensure fast query performance even on massive datasets.
Optimize data storage and compute resources to balance performance with cost efficiency. You'll implement partitioning strategies, compression techniques, and data archival policies that minimize storage costs while maintaining query performance and data accessibility.
Evaluate and implement emerging data technologies that can enhance Pattern's data capabilities. You'll stay current with industry trends, prototype new solutions, and advocate for technology adoption when it provides clear business value and competitive advantage.
Drive innovation in data architecture by exploring modern approaches like data mesh, lakehouse architectures, and real-time analytics platforms. You'll contribute to Pattern's data strategy and help shape the evolution of our data infrastructure to support future business needs.
REQUIRED QUALIFICATIONS
Education & Experience
Bachelor's Degree in Data Science, Data Analytics, Information Management, Computer Science, Information Technology, related field, or equivalent professional experience. We value both formal education and practical experience, recognizing that exceptional data engineering skills can be developed through various paths.
Overall experience should be more than 7+ years in data engineering, software engineering, or related technical roles with progressive responsibility and increasing complexity of data challenges. You should have a proven track record of building production data systems at scale.
Technical Expertise - Core Skills
3+ years of experience working with SQL and Python. You should be highly proficient in:
- SQL: Complex queries with joins, subqueries, window functions, CTEs, stored procedures, query optimization, and performance tuning
- Python: Data processing with pandas, PySpark, data validation, API integrations, scripting, and automation
3+ years of experience implementing data pipelines using modern data architectures. You should have hands-on experience building ETL/ELT workflows, implementing data orchestration, handling schema evolution, and managing data pipeline lifecycle from development through production deployment and maintenance.
2+ years of experience working with data warehouses such as Redshift, BigQuery, Snowflake, or similar cloud data warehouse platforms. You should understand data warehouse design principles including dimensional modeling, slowly changing dimensions, fact tables, and optimization techniques specific to columnar databases.
Experience with open-source based data architectures including Spark, Hive, Trino/Presto, or similar big data processing frameworks. You should be comfortable working with distributed computing concepts, understand Spark internals, and know how to optimize Spark jobs for performance.
Technical Expertise - Additional Requirements
Excellent software engineering and scripting knowledge including version control (Git), CI/CD practices, testing frameworks, code quality standards, and software development lifecycle. You should write clean, maintainable, and well-documented code.
Expertise with data systems working with massive data volumes from various data sources. You should have experience handling petabyte-scale datasets, understand data partitioning strategies, and know how to design systems that can scale horizontally as data volumes grow.
Strong understanding of data modeling including relational modeling, dimensional modeling, data normalization/denormalization, schema design, and data type optimization for different use cases.
Experience with cloud platforms particularly AWS services including S3, EC2, EMR, Redshift, Lambda, Glue, Kinesis, SQS, SNS, and CloudFormation or similar infrastructure as code tools.
Leadership & Communication
Ability to lead a team of Data Engineers, providing technical mentorship, conducting code reviews, making architectural decisions, and fostering a collaborative team environment focused on continuous improvement and technical excellence.
Strong communication skills (both in presentation and comprehension) along with the aptitude for cross-collaboration across data management and analytics domains. You should effectively communicate complex technical concepts to both technical and non-technical audiences, document technical designs, and present data solutions to stakeholders.
Ability to work independently and take ownership of data products from conception through production deployment and ongoing maintenance, while also collaborating effectively with cross-functional teams.
PREFERRED QUALIFICATIONS
Advanced Technical Skills
Experience working with time series databases such as InfluxDB, TimescaleDB, or Prometheus for handling time-stamped data common in eCommerce analytics including pricing trends, inventory levels, and sales metrics over time.
Advanced knowledge of SQL including the ability to write stored procedures, triggers, user-defined functions, analytic/windowing functions, query tuning, and execution plan analysis. You should be able to optimize complex queries processing billions of rows.
Advanced knowledge of Snowflake including the ability to write and orchestrate streams and tasks, implement Snowpipe for continuous data loading, use Snowflake's unique features like time travel and zero-copy cloning, and optimize warehouse configurations for different workloads.
Background in Big Data, non-relational databases, Machine Learning, and Data Mining. Experience with NoSQL databases (MongoDB, Cassandra, DynamoDB), understanding of ML model requirements, feature engineering, and data science workflows is highly valuable.
Cloud & Modern Platform Experience
Experience with cloud-based technologies including:
- AWS Services: SNS, SQS, SES, S3, Lambda, Glue, EMR, Kinesis, Athena, and CloudWatch
- Infrastructure as Code: Terraform, CloudFormation, or similar tools
- Container technologies: Docker, Kubernetes, or ECS
Experience with modern data platforms like:
- Data Warehouses: Redshift, Snowflake, BigQuery with deep optimization knowledge
- NoSQL Databases: Cassandra, DynamoDB, MongoDB for specific use cases
- Orchestration: Apache Airflow, Prefect, Dagster for workflow management
- Processing Engines: Apache Spark, Flink, or similar distributed computing frameworks
- Search & Analytics: ElasticSearch, OpenSearch for full-text search and analytics
Data Quality & Governance Expertise
Expertise in Data Quality and Data Governance including:
- Implementation of data quality frameworks and automated validation
- Data cataloging and metadata management solutions
- Data lineage tracking and impact analysis
- Master data management and data dictionary creation
- Compliance with data privacy regulations (GDPR, CCPA)
- Data classification and sensitive data handling
Experience with data observability tools like Monte Carlo, Great Expectations, or similar platforms for monitoring data health and catching data quality issues proactively.
OUR CORE VALUES
At Pattern, our core values define our culture and guide our daily work. We seek team members who embody these principles:
Data Fanatics
Our edge is always found in the data. As a Senior Data Engineer, you'll be at the heart of Pattern's data-driven culture. You'll build the infrastructure that enables data-informed decisions across the organization, ensuring our teams have access to accurate, timely, and actionable data that drives partner success.
Partner Obsessed
We are obsessed with partner success. Every data pipeline you build, every data model you design, and every optimization you implement ultimately serves our partners' success. You'll ensure data quality and availability that enables Pattern to deliver exceptional results for the global brands depending on our platform.
Team of Doers
We have a bias for action. We don't just plan data solutions—we build them, deploy them, and iterate on them. We take ownership of data products, collaborate effectively to solve problems, and hold ourselves accountable for delivering reliable data infrastructure that powers Pattern's business.
Game Changers
We encourage innovation. We're constantly exploring new data technologies, architectural patterns, and optimization techniques. We challenge conventional approaches, experiment with emerging solutions, and push the boundaries of what's possible with data engineering to maintain our competitive advantage.
WHY PATTERN?
Growth & Opportunity
The company is a rocket ship experiencing phenomenal growth. Pattern is one of the fastest-growing tech companies in North America, and you'll be part of the data engineering team enabling this growth through scalable, reliable data infrastructure.
We have tailwinds and a long runway; we're barely scratching the surface. The eCommerce acceleration market is massive and growing, and Pattern is positioned to capture significant market share. Your data engineering work will scale alongside this growth.
We have big opportunities that will get you energized and excited. You'll work on challenging data problems at massive scale, processing 46 trillion data points, building real-time analytics systems, and enabling AI/ML models that power strategic decisions for global brands.
Technical Excellence
Work with cutting-edge data technologies including Snowflake, Apache Spark, AWS cloud services, streaming platforms, and modern data orchestration tools. You'll have opportunities to experiment with emerging technologies and apply them to production use cases.
Solve complex data challenges at scale that few companies experience. You'll design systems handling petabyte-scale data volumes, build real-time processing pipelines, and optimize queries across massive datasets.
Impact business outcomes directly through your data engineering work. You'll see how your pipelines and data products enable better decisions, drive revenue optimization, and contribute to partner success.
Benefits & Work Environment
Great benefits including time off, insurance, competitive pay. Pattern offers comprehensive benefits packages designed to support your wellbeing and work-life balance.
Collaborative, inclusive culture recognized as one of Newsweek's Global Most Loved Workplaces®. You'll work with talented engineers, data scientists, and business professionals who are passionate about data and partner success.
Professional development opportunities including training, certifications, conferences, and continuous learning resources to advance your data engineering career.
Global impact working with data from 60+ marketplaces worldwide, supporting hundreds of global brands, and solving data challenges across diverse eCommerce ecosystems.
LOCATION & WORK ENVIRONMENT
This is a full-time, on-site position based in Pune, India. You'll work from Pattern's office environment, collaborating with local data engineering teams while also partnering with distributed teams across Pattern's global operations.
The role offers standard working hours with flexibility as needed to coordinate with global teams and handle critical data pipeline issues. Pattern provides a modern workspace with high-performance development tools, data engineering platforms, and collaborative facilities that enable productive, innovative work.
DIVERSITY & EQUAL OPPORTUNITY
Pattern provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state, or local laws.
Pattern is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. We believe diverse perspectives make our data solutions better, our team stronger, and our culture richer.
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 who consider the complete picture of your qualifications, experience, and potential fit with our team. If you would like more information about how your data is processed, please contact us.
HOW TO APPLY
Ready to take your data engineering career to the next level at one of North America's fastest-growing tech companies? Join Pattern and build data infrastructure that processes trillions of data points and powers global eCommerce success.
To apply:
- Submit your updated resume highlighting your data engineering experience, technical skills, and key accomplishments including scale of data systems you've built
- Include links to your GitHub profile or portfolio showcasing data engineering projects, code samples, or technical contributions
- Provide a cover letter explaining why you're excited about this role and how your experience aligns with Pattern's data engineering needs
- Be prepared to discuss your experience with specific technologies, architectural decisions you've made, and challenges you've solved in data engineering
Interview Process:
- Initial Screening (30 minutes): Discussion about your background, experience with data technologies, and interest in Pattern
- Technical Assessment: SQL/Python coding challenge or data pipeline design exercise
- Technical Deep Dive (2-3 rounds):
- Data pipeline architecture and design discussion
- SQL query optimization and data modeling evaluation
- System design for large-scale data processing
- Leadership Interview: Discussion about mentoring experience, collaboration approach, and team leadership
- Final Interview: Meet with senior data leadership to discuss role expectations and mutual fit
We review applications continuously and encourage early submissions. We provide timely feedback and strive to make the interview process informative and engaging for candidates.
CONTACT INFORMATION
Join Pattern's data engineering team and help us leverage data to transform global eCommerce. Your expertise will power decisions for hundreds of brands and process trillions of data points—apply today!
Pattern | Accelerating Global eCommerce Through Data Excellence
This job description is effective as of December 2024 and may be updated to reflect evolving business needs and opportunities.
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