AWS Data Engineer

2 days ago

India Zensar Technologies Full time ₹ 12,00,000 - ₹ 36,00,000 per year
Description

AWS Data Engineer - GCH 

must have:

  1. Proficiency with Matillion ETL: Using the Matillion ETL platform for data integration.
  2. Cloud Data Warehouses: Familiarity with cloud data warehouses like Snowflake, AWS Redshift, or Google BigQuery.

Key Responsibilities:

  • Design & Develop Data Pipelines: Build and optimize scalable, reliable, and automated ETL/ELT pipelines using AWS services (e.g., AWS Glue, AWS Lambda, Redshift, S3) and Databricks.
  • Cloud Data Architecture: Design, implement, and support in maintaining data infrastructure in AWS, ensuring high availability, security, and scalability. Work with lake houses, data lakes, data warehouses, and distributed computing.
  • DBT Core Implementation: Lead the implementation of DBT Core to automate data transformations, develop reusable models, and maintain efficient ELT processes.
  • Data Modelling: Build efficient data models to support required analytics/reporting.
  • Optimize Data Workflows: Monitor, troubleshoot, and optimize data pipelines for performance and cost-efficiency in cloud environments. Utilize Databricks for processing large-scale data sets and streamlining data workflows.
  • Data Quality & Monitoring: Ensure high-quality data by implementing data validation and monitoring systems. Troubleshoot data issues and create solutions to ensure data reliability.
  • Automation & CI/CD: Implement CI/CD practices for data pipeline deployment and maintain automation for monitoring and scaling data infrastructure in AWS and Databricks.
  • Documentation & Best Practices: Maintain comprehensive documentation for data pipelines, architectures, and best practices in AWS,  Databricks, and DBT Core. Ensure knowledge sharing across teams.


Skills & Qualifications: 

Required:

  • Bachelor's / master's degree in computer science, Engineering or a related field.
  • 4+ years of experience as a Data Engineer or in a similar role.
  • Extensive hands-on experience with AWS services (S3, Redshift, Glue, Lambda, Kinesis, etc.) for building scalable and reliable data solutions.
  • Advanced expertise in Databricks, including the creation and optimization of data pipelines, notebooks, and integration with other AWS services.
  • Strong experience with DBT Core for data transformation and modelling, including writing, testing, and maintaining DBT models.
  • Proficiency in SQL and experience with designing and optimizing complex queries for large datasets.
  • Strong programming skills in Python/PySpark, with the ability to develop custom data processing logic and automate tasks.
  • Experience with Data Warehousing and knowledge of concepts related to OLAP and OLTP systems.
  • Expertise in building and managing ETL/ELT pipelines, automating data workflows, and performing data validation.
  • Familiarity with CI/CD concepts, version control (e.g., Git), and deployment automation.
  • Having worked under Agile project environment

Preferred:

  • Experience with Apache Spark and distributed data processing in Databricks.
  • Familiarity with streaming data solutions (e.g., AWS Kinesis, Apache Kafka).

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