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Job Location: Bangalore
- 1+ years of experience as a Data Engineer or in a similar role
- Experience with data warehousing, and building ETL pipelines
- Experience in SQL
- Design, implement and operate large-scale, multi-tiered ,high-volume, high-performance data solutions supporting Analytics, reporting and Machine Learning
- Gather business and functional requirements and translate them to robust, scalable, and flexible data solutions
- Implement data ingestion routines from a wide variety of data sources using best practices in data modeling, ETL/ELT processes by leveraging SQL and AWS technologies and big data tools.
- Develop data pipelines to support data analytics, machine learning model training and other offline, batch workflows.
- Help continually improve existing DW architecture, reporting and analysis processes, automate or simplify self-service modeling and production support for customers.
- Perform code and design reviews of the work of other data and BI Engineers, including feedback on architecture and design issues, as well as integration, performance and scalability
Amazon Retail Consumables Analytics & Data Engineering (CADE) team is looking for an experienced and technically skilled Data Engineer.
This role will be supporting the data engineering initiatives of Retail Consumables Category Productivity (CCP) ) divisions of consumables business as the primary business stakeholder. Consumables is one of the pillars of amazon core retail and fastest growing business. As a DE in this team, you will be responsible for developing the data architecture components and big data solutions that scale for the ever-evolving data needs. You will be instrumental in applying AWS data engineering service and tools offerings to solve challenging problems in big data processing, data warehouse design, and enabling self-service.
As a Data Engineer on the team you will focus on automation and optimization for all areas of DW/ETL maintenance and deployment. You will work closely with the the data analytics and science teams, other business stakeholders and software engineering teams across the business to align the Data Engineering roadmaps and to solve many unique business problems. You will use creative problem solving to deliver actionable output in data gathering, transformation, ingestion and storage. As a senior engineer, you will mentor junior data engineers, identify and solve issues with the current design, scaling and storage solutions and continuously look around corners to raise the bar on data capabilities to meet the current and future data needs of the business. You will be a key contributor in the design and development of scalable architectural components and solve challenging data problems by applying both in-house and AWS services and tools.
A qualified candidate must have demonstrated ability to manage large-scale data modeling projects, identify requirements and tools, and build scalable data warehousing solution and manage AWS resources. If you love solving challenging problems and like to move fast in a growing and changing environment, this role is right fit for you. We use data to guide our decisions and we always push the technology and process boundaries of what is feasible on behalf of our customers. The most successful members of our team are obsessed with helping our customers in creative ways, bring clarity to ambiguity through data driven experimentation, drive process improvements by automations, learn and adopt new technologies and think big to build solutions extensible enough to handle existing and upcoming use cases.
Key job responsibilities
Key job responsibilities
- Collaborate with Data Science and Analytics teams in the org in identifying the business requirements
- Design and develop the data architecture and influence the Data Engineering roadmap of the supporting businesses
- Design and development of data models and data pipelines according to the business needs
- Establish and drive data engineering best practices and set standards.
- Evaluate end-to-end data designs for strengths and weaknesses of the data systems (data quality, scalability, latency, security, performance, data integrity, etc.)
- Establish and clearly communicate organizational vision, goals and success measures to business stakeholders
- Develop and mentor a team of high-performance junior data engineers
- Report on status of development, quality, operations, and system performance to leadership and business stakeholders
- Experience working with AWS big data technologies like Redshift, EMR, Athena, glue
- Knowledge of software engineering best practices across the development lifecycle, including agile methodologies, coding standards, code reviews, source management, build processes, testing, and operations
- Experience providing technical leadership and mentoring other engineers for best practices on data engineering
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