Data Specialist

1 month ago

bangalore, India Brillio Full time
About Brillio:
Brillio is one of the fastest growing digital technology service providers and a partner of choice for many Fortune 1000 companies seeking to turn disruption into a competitive advantage through innovative digital adoption. Brillio, renowned for its world-class professionals, referred to as "Brillians", distinguishes itself through their capacity to seamlessly integrate cutting-edge digital and design thinking skills with an unwavering dedication to client satisfaction.
Brillio takes pride in its status as an employer of choice, consistently attracting the most exceptional and talented individuals due to its unwavering emphasis on contemporary, groundbreaking technologies, and exclusive digital projects. Brillio's relentless commitment to providing an exceptional experience to its Brillians and nurturing their full potential consistently garners them the Great Place to Work® certification year after year.
Azure Data Specialist
Primary Skills
Pyspark, Advance Sql, Databricks, Aws, feature engineering
Job Description
As a Data Engineer, you’ll play a critical role in designing, building, and maintaining data pipelines and systems. Your work will enable efficient data collection, storage, and processing, supporting data scientists, analysts, and business stakeholders. In this role, you’ll work with cutting-edge technologies to handle large volumes of data and ensure its accessibility and accuracy.
Requirements:
5 years’ experience with SQL required with building ETLs and process in Databricks and Data Factory
5 years’ experience designing and implementing scalable ETL processes.
3 years’ experience with modern Big Data Analytics using Data Lake, Spark and formats like Parquet.
Building data pipelines in Azure Data Factory/Synapse Analytics/Spark.
Responsibilities:
Design and Build Data Models:
Develop data models that align with business requirements.
Create efficient and scalable data structures to support data processing.
Data Ingestion and Processing:
Design and maintain data ingestion pipelines.
Implement data processing systems to transform raw data into usable formats.
Feature Engineering:
Collaborate with data scientists to engineer features from raw data.
Extract relevant information and create new features to enhance predictive models.
Data Warehousing:
Work with data warehouses to collect and store data from various sources.
Ensure data consistency and accuracy for meaningful business insights.
Cloud Computing:
Familiarity with cloud computing tools (e.g., AWS, Azure, Google Cloud) for hosting and managing data.
Deploy data solutions on cloud servers.
Big Data Technologies:
Proficiency in handling large datasets using tools like Apache Spark and Apache Hadoop.
Optimize data storage and analysis processes.
Database Management:
Build and maintain databases (SQL, NoSQL, or data lakes).
Ensure data integrity and security.
Collaboration:
Work closely with cross-functional teams (data scientists, analysts, and business stakeholders) to address data-related challenges.
Communicate effectively to understand requirements and deliver solutions.
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