Cloud Engineer

4 weeks ago

India Delphic (South Asia) Full time

Job Summary:

We are looking for a highly skilled AWS Redshift Engineer with over 4 years of experience to join our data engineering team. The ideal candidate will have strong expertise in Amazon Redshift and associated AWS services to design, implement, and optimize large-scale data warehousing solutions. You will be responsible for building and maintaining scalable, high-performance data systems that support critical business operations and data-driven insights.

Key Responsibilities:

  • Design and implement Amazon Redshift-based data warehousing solutions to handle large volumes of structured and semi-structured data.
  • Develop and maintain ETL processes to extract, transform, and load data into Redshift from various data sources using tools like AWS Glue, Lambda, or custom Python/SQL scripts.
  • Optimize Redshift clusters for performance, including query tuning, workload management, distribution styles, and partitioning strategies.
  • Collaborate with data architects and data modelers to design efficient database schemas that support analytics and reporting.
  • Manage Redshift infrastructure including scaling, snapshot management, and monitoring using AWS services like CloudWatch, CloudTrail, and SNS.
  • Ensure data security and compliance through proper encryption, access controls, and user permissions following AWS best practices.
  • Monitor and troubleshoot Redshift performance issues, propose and implement solutions for query optimization and cost efficiency.
  • Integrate Redshift with other AWS services, such as S3, Kinesis, and RDS, to build scalable data pipelines.
  • Develop and maintain documentation of data architecture, processes, and workflows.
  • Collaborate with cross-functional teams (data scientists, analysts, and business stakeholders) to define and meet their data needs.
  • Stay updated with the latest features and best practices of AWS Redshift and the broader AWS ecosystem.

Required Skills & Qualifications:

  • 4+ years of experience in data engineering, with at least 2+ years focused on AWS Redshift.
  • Hands-on experience with Amazon Redshift, including:
  • Redshift Cluster setup, scaling, and management
  • Performance tuning (WLM, distribution keys, sort keys)
  • Writing optimized SQL queries and stored procedures
  • Strong experience with ETL tools and processes, including AWS Glue, AWS Lambda, or similar technologies.
  • Proficiency in SQL for complex query writing and data manipulation.
  • Knowledge of data warehousing concepts, star and snowflake schemas, and database design best practices.
  • Experience with data lake architectures using AWS S3, and integrating Redshift with S3 and other AWS services.
  • Strong understanding of data security (encryption, IAM roles, VPCs, security groups) and AWS networking.
  • Experience with monitoring and automation tools, such as AWS CloudWatch, CloudFormation, or Terraform.
  • Familiarity with Python or Scala for scripting and automation in the AWS environment.
  • Experience with data migration, database replication, and backup strategies in a cloud environment.

Preferred Qualifications:

  • AWS Certified Solutions Architect, Database Specialty, or Data Analytics certifications.
  • Experience with BI tools like Tableau, QuickSight, or Power BI for reporting and analytics integration.
  • Familiarity with data governance and regulatory compliance (GDPR, HIPAA, etc.).
  • Knowledge of other AWS services, such as Athena, EMR, or Kinesis, for data processing and analysis.
  • Experience with CI/CD pipelines and deploying data infrastructure in an agile environment.
  • Familiarity with machine learning workflows and integration with Redshift for advanced analytics.

Soft Skills:

  • Strong analytical and problem-solving abilities.
  • Excellent communication skills to interact with both technical and non-technical stakeholders.
  • Ability to work independently and as part of a collaborative team.
  • Detail-oriented, with a passion for optimizing performance and efficiency.

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