Azure Data Engineer

Role: Azure Data Engineer

Exp Required: 6-10 years

Location: PAN INDIA

Tech stack: Strong SQL, Azure Data Factory, databricks, python, pyspark

Responsibility:

• Create and maintain optimal data pipeline architecture,
• Assemble large, complex data sets that meet functional / non-functional business requirements.
• Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.
• Build the infrastructure required for optimal ingestion, transformation, and Publishing of data from a wide variety of data sources using Python/Spark and AWS big data technologies.
• Build analytics tools that utilize the data pipeline to provide actionable insights into customer acquisition, operational efficiency and other key business performance metrics.
• Work with stakeholders including the Executive, Product, Data and Design teams to assist with data-related technical issues and support their data infrastructure needs.
• Keep our data separated and secure across national boundaries through multiple data centers and AWS regions.
• Create data tools for analytics and data scientist team members that assist them in building and optimizing our product into an innovative industry leader.
• Work with data and analytics experts to strive for greater functionality in o ur data systems

Must have:

• 5 Yrs + of IT Experience building Data Applications
• Advanced working SQL, Python/PySpark knowledge and experience working with relational databases, query authoring (SQL) as well as working familiarity with a variety of databases.
• Experience of working in Databricks
• Experience building and optimizing Cloud big data data pipelines, architectures and data sets.
• Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement.
• Strong analytic skills related to working with unstructured datasets.
• Experience in Data Modeling
• Experience supporting and working with cross-functional teams in a dynamic environment. and knowledge of one or more from the below