Senior Data Architect Role

1 day ago

Hyderabad, Telangana, India beBeeDataModel Full time ₹ 2,00,00,000 - ₹ 3,00,00,000
Enterprise Data Model Architect

As a senior data architect, you will be responsible for designing and implementing data models that support the company's business objectives.

Key Responsibilities:

  • Develop conceptual, logical, and physical data models for various platforms, including SQL Data Warehouse, EMR, Spark, DataBricks, Snowflake, Azure Synapse, and other Cloud data warehousing technologies.
  • Create data design/modeling documentation of metadata (business definitions of entities and attributes) and construct database objects for baseline and investment-funded projects.
  • Provide data analysis, requirements gathering, solution development, and design reviews for enhancements to or new applications/reporting.
  • Support project contractors in orienting them to standards, best practices, and tools.
  • Contribute to project cost estimates by evaluating the size and complexity of changes or new development with senior team members.
  • Design physical and logical data models with an extensible philosophy to support future use cases with minimal rework.

Required Skills and Qualifications:

  • 8+ years of technology experience with at least 4+ years of data modeling and systems architecture.
  • 3+ years of experience with Data Lake Infrastructure, Data Warehousing, and Data Analytics tools.
  • 4+ years of experience developing enterprise data models.
  • Experience in building solutions in the retail or supply chain space.
  • Expertise in data modeling tools (ER/Studio, Erwin, IDM/ARDM models).
  • Experience with integration of multi-cloud services (Azure) with on-premises technologies.
  • Experience with data profiling and data quality tools like Apache Griffin, Deequ, and Great Expectations.
  • Experience building/operating highly available, distributed systems of data extraction, ingestion, and processing of large data sets.

Benefits:

  • Opportunity to work with a cutting-edge technology stack.
  • Collaborative and dynamic work environment.
  • Chance to contribute to the growth and success of the company.

Others:

  • Partnering with IT, data engineering, and other teams to ensure the enterprise data model incorporates key dimensions needed for proper management.
  • Driving collaborative reviews of design, code, data, security features implementation performed by data engineers.
  • Assisting with data planning, sourcing, collection, profiling, and transformation.
  • Creating Source To Target Mappings for ETL and BI developers.
  • Showcasing expertise in data at all levels: low-latency, relational, and unstructured data stores; analytical and data lakes; data str/cleansing.

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