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Senior Analytics Data Engineer

hace 2 meses

Tlaquepaque, Jalisco, México Hewlett Packard A tiempo completo
About the Role

We are seeking a highly skilled Senior Data Engineer to join our team at Hewlett Packard. As a Senior Data Engineer, you will play a key role in designing, building, and operating high-performance Business Intelligence (BI) centric solutions using our comprehensive analytics platform.

Key Responsibilities
  • Lead Data Engineering Teams: Lead one or more project teams of data engineers for all stages of design and development for complex, secure, and performant data solutions and models, including design, analysis, coding, testing, and integration of structured and unstructured data.
  • Review and Evaluate Designs: Review and evaluate designs and project activities for compliance with architecture, security, and quality guidelines and standards; provide tangible feedback to improve product quality and mitigate failure risk.
  • Drive Innovation: Drive innovation and integration of new technologies into projects and activities in the big data space.
  • Create Optimal Data Pipelines: Create and maintain optimal data pipeline/ETL architecture.
  • Collaborate with Business Stakeholders: Collaborate with businesses, application, and process owners, and product team members to define requirements and design solutions for the company's big data and analytics solutions.
  • Build Infrastructure: Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using MS SQL/SSIS and Big Data technologies.
  • Develop Technical Solutions: Develop technical solutions in MS SQL and cloud-based technologies and ensure they are designed and built to be sustainable and robust.
  • Perform Data Modeling: Perform data modeling and prepare data in databases for use in various analytics tools and configure and develop data pipelines to move and optimize data assets.
  • Provide Technical Support: Provide necessary technical support through all phases of solution life cycle.
  • Handle Complex Issues: Independently handle complex issues with minimal supervision, while escalating only the most complex issues to appropriate staff.
Requirements
  • Must-Have Skills: SQL Programming, ETL (SSIS/Azure Data Factory/AWS Glue), Data Warehouse, Database Architecture, Analytical knowledge, Problem Solving, AWS/Azure/GCP.
  • Reporting Tools: Tableau/Power BI, Excel Charts, etc.
  • Nice-to-Have Skills: Databricks, Github, Jira Confluence, Big Data technologies, Airflow, Spark, Kafka, etc.
  • Experience: Experience developing data or software applications including analysis, design, coding, testing, deploying, and supporting of applications.
  • Cloud Experience: Experience working with Google Cloud Platform (GCP), AWS, MS SQL.
  • Big Data Tools: Basic knowledge/experience with big data tools: Azure, Airflow, Spark, Kafka, etc.
  • NoSQL and Relational Systems: Fluent in NoSQL & relational based systems.
  • Analytical and Problem-Solving Skills: Excellent analytical and problem-solving skills.
  • Reporting Tools and Data Sources: Experience with reporting tools and data sources.
  • BI Solutions: Proven track record implementing BI solutions.
  • Data Engineering Tools: Extensive experience with data engineering tools, languages, frameworks to mine, cleanse, and explore data.
  • eCommerce Business Value Creation: Strong understanding of eCommerce business value creation by leveraging disparate data sourcing and enabling business decisions.
  • Communication Skills: Excellent communication skills, both written and verbal.
  • Technology to Improve Process and Control: Demonstrated ability to understand and use technology to improve process and control.
  • Data Systems and Solutions: Designing data systems/solutions to manage complex data in complex, distributed, and massively parallel systems.
  • Database Architecture Testing and Methodology: Evaluating forms and processes for database architecture testing and methodology, including writing and execution of test plans, debugging, and testing scripts and tools.
  • Communicate Product Architectures and Design Proposals: Ability to effectively communicate product architectures, design proposals, and negotiate options at senior management levels.
Scope and Impact
  • Collaborate with Peers: Collaborates with peers, data engineers, data scientists, and project team.
  • Interact with High-Level Individual Contributors: Typically interacts with high-level individual contributors, managers, directors, and program core teams.
  • Lead Multiple Projects: Leads multiple projects requiring data engineering solutions development.
  • Drive Design Innovation: Drives design innovation.
Prior Beneficial Experiences
  • Application Programming Interface Development: Experience and skills with application programming interface development.
  • Reporting Tools: Applied experience in reporting tools.
  • Cloud Platforms: Applied experience with cloud platforms.
Education and Experience
  • Bachelor's or Master's Degree: Bachelor's or Master's degree in Computer Science, Information Systems, Engineering, or equivalent.
  • Typical Experience: Typically 6-10 years' experience.