Azure Data Engineer

4 weeks ago


Delhi, India HTC Global Services Full time
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 externalExperiace 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 frameworksExpertise in a scripting language like Python (or similar) and a query language like

SQLKnowledge of scheduling, logging, monitoring, alert frameworksExperience 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 productionDemonstrated proficiency in writing high-quality and scalable code and integrating with git version control systemsExperience leading successful data engineering projects and operationalizing machine learning algorithmsExperience with streaming architectures e.g. Kafka, Stream, PubSub.


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