The Role
Leads the design, development, optimization, and support of ETL/ELT pipelines, cloud data warehouses, data models, and advanced SQL solutions. Partners with analysts, data scientists, and stakeholders to deliver reliable datasets, while implementing testing, documentation, CI/CD, monitoring, and incident resolution practices. Mentors associate engineers and provides technical leadership across data engineering initiatives.
Summary Generated by Built In
Duties & Responsibilities:
- Lead the design, development, and optimization of ETL/ELT pipelines and workflows
- Write, tune, and optimize advanced SQL queries for large-scale data processing
- Build and maintain data warehouses and data models (relational, dimensional, star schema)
- Translate business requirements into robust, well-architected, and reusable data solutions
- Partner with analysts, data scientists, and stakeholders to deliver trusted, actionable datasets
- Implement and maintain unit tests, integration tests, and validation frameworks to ensure pipeline reliability
- Document workflows, and design decisions to support knowledge sharing and operational continuity
- Apply coding standards, CI/CD practices, version control, and peer code reviews to ensure high-quality deliverables
- Proactively monitor, optimize, and troubleshoot pipelines for performance, scalability, and cost efficiency
- Support deployments and handle post-production monitoring and incident resolution
- Mentor associate engineers, providing technical guidance and feedback
Requirements
Basic Qualifications:
- Bachelor’s degree in computer science, Information Systems, Engineering, or a related field
- 4–7 years of hands-on experience in data engineering or related fields
- Expertise in writing complex SQL queries, optimizing, using advanced functionals and turning the performance on cloud data warehouse environment.
- Strong experience with data warehousing concepts, design, and implementation
- Minimum 3 years of hands-on experience with Snowflake or modern cloud data warehouse
- Minimum 2 years of hands-on experience in data modeling
- Minimum 1 year of hands-on Python development (ETL/ELT scripting, OOP, automation)
- Strong knowledge of at least one major cloud platform (AWS, Azure, or GCP)
- Experience with orchestration tools (e.g., Airflow, ADF, Luigi) for workflow management
- Demonstrated ability to lead and mentor teams while managing multiple priorities
- Strong communication and stakeholder management skills
- Strong hands-on experience with data warehousing concepts, design, and implementation
Preferred Qualifications:
- Hands-on experience with DBT (Data Build Tool) for data transformations
- Familiarity with DevOps and CI/CD best practices in data engineering
- Exposure with real-time/streaming platforms (Kafka, Spark Streaming, Flink)
- Exposure to the e-commerce domain or large-scale B2B/B2C environments
- Has the ability to break down problems and estimate time for development tasks
- Experience mentoring and guiding junior engineers
- Understands the technology landscape, up to date on current technology trends and new technology, brings new ideas to the team
- Learns organization vision statement and decision-making framework. Able to understand how team and personal goals/objectives contribute to the organization vision
Skills Required
- Bachelor's degree in computer science, information systems, engineering, or a related field
- 4-7 years of hands-on experience in data engineering or related fields
- Expertise writing and optimizing complex SQL queries for cloud data warehouses
- Strong experience with data warehousing concepts, design, and implementation
- At least 3 years of hands-on experience with Snowflake or a modern cloud data warehouse
- At least 2 years of hands-on experience in data modeling
- At least 1 year of hands-on Python development for ETL/ELT scripting, object-oriented programming, and automation
- Strong knowledge of at least one major cloud platform: AWS, Azure, or GCP
- Experience with workflow orchestration tools such as Airflow, Azure Data Factory, or Luigi
- Ability to lead and mentor teams while managing multiple priorities
- Strong communication and stakeholder management skills
- Hands-on experience with data warehousing concepts, design, and implementation
- Hands-on experience with dbt for data transformations
- Familiarity with DevOps and CI/CD best practices in data engineering
- Exposure to real-time or streaming platforms such as Kafka, Spark Streaming, or Flink
- Exposure to e-commerce or large-scale B2B/B2C environments
- Ability to break down problems and estimate development task timelines
- Experience mentoring and guiding junior engineers
- Awareness of current technology trends and ability to bring new ideas to the team
- Understanding of organizational vision and decision-making frameworks
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The Company
What We Do
Staples India is Staples’ technology and innovation hub in Chennai, building platforms, systems, and digital solutions that support the company’s global operations and future of work. Staples serves consumers and businesses with workplace products and services, including office supplies, janitorial products, technology, furniture, breakroom essentials, print and marketing, shipping, travel, and promotional offerings. Its India teams focus on engineering, eCommerce, process optimization, and enterprise solutions.
