Senior Cloud Engineer

Role & responsibilities

Senior Cloud Data Engineer

Key Responsibilities:

• Design, build, and maintain scalable and secure data pipelines using

  AWS Glue

  ,

  Redshift

  , and

  Python

  .
• Develop and optimize

  SQL queries and stored procedures

  for complex data transformations and migrations.
• Automate infrastructure provisioning and deployment using

  Terraform

  , ensuring repeatability and compliance.
• Architect and implement data lake and data warehouse solutions on AWS.
• Collaborate with cross-functional teams including data scientists, analysts, and DevOps to deliver high-quality data solutions.
• Monitor, troubleshoot, and optimize data workflows for performance, reliability, and cost-efficiency.
• Implement data quality checks, validation frameworks, and monitoring tools.
• Ensure data security, privacy, and compliance with industry standards and regulations.
• Lead code reviews, mentor junior engineers, and promote best practices in data engineering.
• Participate in capacity planning, cost optimization, and performance tuning of cloud data infrastructure.
• Evaluate and integrate new tools and technologies to improve data engineering capabilities.
• Document technical designs, processes, and operational procedures.
• Support business intelligence and analytics teams by ensuring timely and accurate data availability.

Required Skills & Experience:

• 10+ years

  of experience in data engineering or cloud data architecture.
• Strong expertise in

  AWS Redshift

  , including schema design, performance tuning, and workload management.
• Proficiency in

  SQL

  and

  stored procedures

  for ETL and data migration tasks.
• Hands-on experience with

  Terraform

  for infrastructure as code (IaC) in AWS environments.
• Deep knowledge of

  AWS Glue

  for ETL orchestration and job development.
• Advanced programming skills in

  Python

  , especially for data processing and automation.
• Solid understanding of data warehousing, data lakes, and cloud-native data architectures.

Preferred candidate profile

• AWS Certifications (e.g., AWS Certified Data Analytics Specialty, AWS Certified Solutions Architect).
• Experience with CI/CD pipelines and DevOps practices.
• Familiarity with additional AWS services like S3, Lambda, CloudWatch, Step Functions, and IAM.
• Knowledge of data governance, lineage, and cataloging tools (e.g., AWS Glue Data Catalog, Apache Atlas).
• Experience with real-time data processing frameworks (e.g., Kinesis, Kafka, Spark Streaming).