Design, build, and maintain efficient and reliable data pipelines for ingestion, transformation, and delivery.
Optimize data processing workflows using Python, PySpark, and SQL.
Work with cloud-native infrastructure (AWS, Terraform, CloudFormation) to deploy and manage data environments.
Implement best practices for data validation, data quality, and incremental data loading.
Develop event-driven and API-based data ingestion frameworks.
Collaborate with cross-functional teams including analysts, product owners, and data scientists to understand data needs.
Drive performance improvements, scalability, and maintainability of data solutions.
Key Skills & Expertise :
Cloud & Infrastructure :
Proven hands-on experience with AWS Services
Experience using Snowflake for cloud data warehousing
Infrastructure as Code : Terraform / CloudFormation
Familiarity with CI / CD pipelines (Jenkins, Bitbucket, etc.)
Programming & Scripting :
Strong proficiency in Python and PySpark
Excellent SQL skills for complex querying and data modeling
ETL & Data Modelling :
Expertise in building scalable ETL / ELT pipelines
Experience with :
Event-driven architectures
API-based data ingestion
Archival strategies
Incremental data loading
Preferred Qualifications :
Bachelors / Masters degree in Computer Science, Engineering, or related field
Exposure to real-time data streaming tools (Kafka, Kinesis, etc.) is a plus
Familiarity with data governance and compliance frameworks
(ref : hirist.tech)
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Data Engineer • Hyderabad
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