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Company | Pure Storage |
Address | Santa Clara, CA, United States |
Employment type | FULL_TIME |
Salary | |
Category | Computer Hardware Manufacturing,Software Development |
Expires | 2023-06-30 |
Posted at | 11 months ago |
BE PART OF BUILDING THE FUTURE.
- Industry analysts and press applaud Pure’s leadership across these dimensions
- And, our 4,000+ employees are emboldened to make Pure a faster, stronger, smarter company as we go
- For eight straight years, Gartner has named Pure a leader in the Magic Quadrant
- Our customer-first culture and unwavering commitment to innovation have earned us a certified Net Promoter Score in the top 1% of B2B companies globally
- Align with industry leading technology standards to develop solutions capabilities
- Work with data and analytics experts to strive for greater functionality in our data systems
- Lead and Develop solutions to manage core master data and quality,
- Create data tools for analytics and data scientist team members that assist them in building and optimizing our product into an innovative industry leader.
- Keep our data secure while building data products to derive business insights from the data
- Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources into Snowflake
- Assemble large, complex data sets that meet functional / non-functional business requirements
- Communication with internal team members and stakeholders in other time zones for the purpose of requirements clarification and progress reporting
- Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.
- Build Data Quality capabilities for profiling, cleansing and standardizing Master and Reference data from multiple diverse Business systems
- Lead, create, and review technical solution requirements documents
- Pure creates opportunities for your development and career growth.
- Experience with Industry leading MDM & Data Quality tools.
- Experience with object-oriented/object function scripting languages: Python, Java
- Hands-on experience with data modeling (logical, physical data models) and Meta-data.
- Experience building and optimizing ‘big data’ data pipelines, architectures and data sets.
- Build processes supporting data transformation, data structures, metadata, dependency and workload management.
- Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement.
- Hands on experience in implementing Industry leading MDM solution capabilities for Entity Management, Hierarchy Management, Data Cleansing, Match and Merge, etc
- Strong project management and organizational skills.
- Advanced SQL knowledge and experience working with relational databases, query authoring (SQL) as well as working familiarity with a variety of databases.
- Working knowledge of message queuing, stream processing, and highly scalable ‘big data’ data stores.
- Experience with stream-processing systems: Spark-Streaming, Kafka etc.
- Knowledge of DQ Process and Procedures such as Define, Discovery, Profiling, Remediation, and Monitoring
- Strong analytic skills related to working with unstructured datasets.
- Experience with AWS cloud services: Aurora, Kinesis
- Experience supporting and working with cross-functional teams in a dynamic environment.
- Experience with relational SQL and NoSQL databases, including Postgres and Cassandra.
- Knowledge of data governance practices, business and technology issues related to management of enterprise information assets, and approaches related to data protection.
- Hands-on Experience with data quality management capabilities and analysis
- A successful history of manipulating, processing and extracting value from large disconnected datasets.
- Experience with data pipeline and workflow management tools: Airflow, etc.
- We are looking for a candidate with 10+ years of experience in a Data Engineer role, who has attained a Graduate degree in Computer Science, Statistics, Informatics, Information Systems or another quantitative field. They should also have experience using the following software/tools:
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