About this role
YASH Technologies is a leading technology integrator specializing in helping clients reimagine operating models, enhance competitiveness, optimize costs, foster exceptional stakeholder experiences, and drive business transformation. At YASH, we’re a cluster of the brightest stars working with cutting-edge technologies. Our purpose is anchored in a single truth – bringing real positive changes in an increasingly virtual world and it drives us beyond generational gaps and disruptions of the future.
- We are looking forward to hire AWS Professionals in the following areas : Job Descreption: Role Overview We are seeking an 4 to 7 Yrs experienced AWS Data Egnieer 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 strong 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
- Experience in data migration and data modelling.
- AWS Certified Data Analytics – Specialty or AWS Certified Solutions Architect – Associate.
- 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 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.
At YASH, you are empowered to create a career that will take you to where you want to go while working in an inclusive team environment. We leverage career-oriented skilling models and optimize our collective intelligence aided with technology for continuous learning, unlearning, and relearning at a rapid pace and scale. 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