Data Engineer (Azure)

Job Category: Engineer
Job Type: Full Time
Job Location: California - US
Experience: 5 – 8 Years


  • Experience with Azure Synapse, Azure Data lake, Azure Data Factory, Azure Logic
  • Apps and Synapse Dedicated SQL pool.
  • Strong ETL/ELT experience.
  • Solid knowledge of using languages such as SQL, Python
  • Hands-on software development skills e.g. DevOps
  • Solid knowledge of different data storage types e.g. SQL Server, Data lake, No-SQL databases.
  • Expertise in data modeling principles/methods including conceptual, logical & physical Data Models.
  • In depth knowledge of different modeling methodologies and techniques for OLAP and OLTP systems (ER Modeling, Dimensional Modeling).
  • Must be proficient in normalization and denormalization concepts to model different layers of DWH.
  • In-depth knowledge and understanding of all layers of Datawarehouse (Landing,Stage, Dimensional, Semantic, Datamart)
  • Knowledge of Data modeling tools like Erwin (or similar) to design Conceptual, Logical and Physical Data models.
  • Advanced SQL knowledge on concepts like Indexing, Partitioning, Constraints, Keys etc to design optimal data warehouse


  • Build analytical solutions using efficient data collection procedures
  • Consolidate multiple data sources into an integrated platform
  • Design, build and maintain data stores, warehouses, lakes or marts
  • Work well as a team to properly document solutions and designs
  • Optimize existing data pipelines
  • Determine how the various entities are related and develop conceptual diagrams that represent the connections among the entities.
  • Develop a logical data model and validate the model to ensure that it serves the needs of the business application and its consumers.
  • Transform the logical representation of the model into a physical representation by defining physical names,data types for each attribute and entities.
  • Design the right set of distribution strategy ,indexes,partitions and keys (surrogate,Natural keys etc) in order to have optimal performance level for data storage and retrieval.
  • Collaborate with the BI and Analytics teams on creating the optimized data mart and semantic layer.
  • Recommend and establish standards, guidelines and best practices around modeling of dimensional, semantic and data mart layer(e.g. naming convention) to ensure consistency within the system.
  • Work closely with the data engineers to implement data warehouse and ETL Pipelines

Apply for this position

Allowed Type(s): .pdf, .doc, .docx