Senior Manager
1 month ago
Job Description :
Job Summary :
Provide technical leadership and hands-on implementation role in the areas of data techniques including data access, integration, modeling, visualization, mining, design and implementation.
Lead a globally distributed team to deliver high quality solutions. Manage functional & non-functional scope and quality.
Required experience :
- Overall 12+ years of overall technology experience that includes at least 6+ years of hands-on software development, data engineering, and systems architecture.
- Excellent understanding of data technologies landscape
- Well-versed with the pros and cons of various database technologies like Relational, NO SQL, and Columnar databases
- Proven experience (8+ years) in leading analytics, MDM, data platform with a track record of successful project delivery, with a Bachelors Degree or equivalent in Computer Sciences, Data Analytics, Management Information Systems, or related quantitative field in Data Engineering.
- Demonstrated experience managing and migrating data warehousing capabilities to the Azure or similar platforms.
- Experience in BI & Enterprise Data Platform consisting of Data cube, Dashboards & Reporting, Enterprise Semantic Layer, ETL, Raw/Ingestion Data Layer, Data Lake, Data Warehouse, Data Engineering, Mobile capabilities, Enterprise Metrics
- Experience in multi-dimensional modelling like star schema, snowflakes, normalized and denormalized models
- Experience in one or more ETL, BI, Analytics, and advanced visualization technologies
- Experience with data lake infrastructure, data warehousing, and data analytics tools.
Job Responsibilities :
- Partner with data engineers, business leaders, and solutions architects to develop technical architectures for strategic enterprise projects and initiatives.
- Provide inputs to define and execute a strategic roadmap for enterprise data architecture by identifying the current landscape and future business goals
- Provide technical leadership and hands-on implementation role in the areas of data techniques including data access, integration, modelling, visualization, mining, design, and implementation.
- Evolve the architectural capabilities and maturity of the data platform by engaging with enterprise architects and strategic internal and external partners.
- Manage and scale data pipelines from internal and external data sources to support new product launches and drive data quality across data products
- Specify and implement best practices around systems integration, security, performance, and data management
- Create data products for data science and business analyst team members to improve their productivity
- Foster a culture of sharing, re-use, and design for scale, stability, and operational efficiency of data and analytical solutions
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