Jobs

    Azure Data Engineer - India - HTC Global Services

    HTC Global Services
    HTC Global Services India

    1 week ago

    HTC Global Services background
    Technology / Internet
    Description
    • At least 6 years' experience driving impact in a similar capacity at companies creating cutting edge tech using Azure Cloud.
    • Azure Data Factory Pipelines - Create new Azure Data Factory pipelines in cloud based data warehousing systems such as Azure Synapse.
    • Experience with Azure services: Azure Data Lake Gen 2, Data factory, Data Fllows, and Synapse (Azure SQL DW).
    • Data Quality and Anomaly Detection - Improve existing tools (dbt cloud) to measure data quality through metrics and automatic alerting.
    • Experience in working with Azure Databricks environment for data transformation.
    • Experience in working with unstructured data (text) and making data available for down stream NLP analysis.
    • Data Modeling - Partner with data consumers to improve existing data models and build different facets of the business for analytic use cases, Build star and snowflake schemas.
    • Development of data pipelines to third party API's both internal providers and external
    • Experiace in working with NoSQL data bases like MongoDB and pull data from those databases.
    • Expertise building data pipelines on large complex data sets using Spark or other open source frameworks
    • Expertise in a scripting language like Python (or similar) and a query language like SQL
    • Knowledge of scheduling, logging, monitoring, alert frameworks
    • Experience in Source/Target: ADLSGen2, PostGres DB, Azure SQL DW.
    • Orchestration Using Databricks Jupyter Notebooks preferred.
    • Experience working in large scale/distributed SQL, NoSQL (MongoDB) environments.
    • Experience in modeling and implementing ETL / ELT on columnar MPP database technologies.
    • Experience with Agile software development process.

    Preferred:

    • Proven experience deploying machine learning algorithms to production
    • Demonstrated proficiency in writing high-quality and scalable code and integrating with git version control systems
    • Experience leading successful data engineering projects and operationalizing machine learning algorithms
    • Experience with streaming architectures e.g. Kafka, Stream, PubSub.
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