As a Data Engineer will be responsible for assessing complex new data sources and quickly turning these into business insights. You also will support the implementation and integration of these new data sources into our Azure Data platform.

Responsibilities:

You are detailed reviewing and analyzing structured, semi-structured and unstructured data sources for quality, completeness, and business value.
You design, architect, implement and test rapid prototypes that demonstrate value of the data and present them to diverse audiences.
You participate in early state design and feature definition activities.
Responsible for implementing robust data pipeline using Microsoft, Databricks Stack
Responsible for creating reusable and scalable data pipelines.
You are a Team-Player, collaborating with team members across multiple engineering teams to support the integration of proven prototypes into core intelligence products.
You have strong communication skills to effectively convey complex data insights to non-technical stakeholders.
You have an experience working collaboratively in cross-functional teams and manage multiple projects simultaneously.

Skills:

Advanced working knowledge and experience with relational and non-relational databases.
Experience building and optimizing Big Data pipelines, architectures, and datasets.
Strong analytic skills related to working with structured and unstructured datasets.
Hands-on experience in Azure Databricks utilizing Spark to develop ETL pipelines.
Strong proficiency in data analysis, manipulation, and statistical modeling using tools like Spark, Python, Scala, SQL, or similar languages.
Strong experience in Azure Data Lake Storage Gen2, Azure Data Factory, Databricks, Event Hub, Azure Synapse.
Familiarity with several of the following technologies: Event Hub, Docker, Azure Kubernetes Service, Azure DWH, API Azure, Azure Function, Power BI, Azure Cognitive Services.
Azure DevOps experience to deploy the data pipelines through CI/CD.

Qualifications and Experience:

Minimum 5-7 years of practical experience as Data Engineer.
Bachelor’s degree in computer science, software engineering, information technology, or a related field.
Azure cloud stack in-production experience.