We are looking forward to hire AWS Professionals in the following areas :

Job Descreption:

Role Overview

We are seeking an experienced AWS Data Architect with strong hands-on expertise in designing, building, and optimizing scalable data lake and analytics platforms on AWS. The ideal candidate will combine deep technical proficiency in AWS services with a solid understanding of data architecture principles, governance, and best practices for analytical enablement .

Required Skills :

- Proven experience architecting and implementing AWS data lake and analytics ecosystems.
- Hands-on expertise in AWS Glue, S3, Athena, Lambda, Redshift, and Lake Formation.
- Strong programming and ETL skills using PySpark / Python.
- Deep understanding of data modeling, data ingestion patterns, and schema evolution.
- Knowledge of data governance, security, and compliance frameworks in cloud environments.
- Familiarity with CI/CD, IaC, and DevOps tools (CDK, Terraform, GitHub Actions, CodePipeline).
- Experience with data quality frameworks (Deequ, Great Expectations).
- Strong problem-solving, analytical, and communication skills.

Preferred Qualifications

- At least 5-7 years of experience in data architecture and data modelling.
- AWS Certified Data Analytics - Specialty or AWS Certified Solutions Architect - Professional.
- Proven experience with database management systems and data warehousing.
- Strong understanding of data governance and data quality principles.
- Excellent problem-solving and analytical skills.
- Experience with data modelling tools and techniques.

Responsibilities

- Architect and Design:



Define and implement scalable, secure, and cost-efficient AWS-based data lake architectures using S3, Glue, Athena, and Lake Formation.
- Data Engineering: Develop robust ETL/ELT pipelines using PySpark, Glue, and Lambda for batch and near-real-time data ingestion and transformation.
- Data Modeling: Design logical and physical data models, implement schema evolution, partitioning strategies, and efficient metadata management.
- Manage the complete data lifecycle from raw ingestion to curated and analytical layers ensuring data quality, lineage, and traceability.
- Integration: Enable seamless data consumption by downstream systems such as Redshift Spectrum, QuickSight, SageMaker, and other BI platforms.
- Enforce robust data governance, access control, and compliance through IAM, KMS, CloudTrail, and Lake Formation.
- Data Quality: Implement and automate data validation frameworks using tools such as Deequ or Great Expectations.
- Automation & DevOps: Build infrastructure as code (IaC) using AWS CDK or Terraform, and orchestrate CI/CD pipelines with GitHub Actions or AWS CodePipeline.
- Monitoring & Optimization: Set up observability, performance tuning, and cost optimization through CloudWatch, Glue job optimization, and Athena query tuning.

Our Hyperlearning workplace is grounded upon four principles

- Flexible work arrangements, Free spirit, and emotional positivity
- Agile self-determination, trust, transparency, and open collaboration
- All Support needed for the realization of business goals,
- Stable employment with a great atmosphere and ethical corporate culture

📌 Module Lead - AWS (Hyderabad)
🏢 Yash Technologies
📍 Hyderabad