AWS Tech Lead - Data Engineering & Machine Learning

Tech Lead - AWS Job

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 Glue Professionals in the following areas :

 

Experience

8+ Years

Job Description

Key Responsibilities:

Data Engineering:

·Data LakeHouse:

o Simplify analytics and AI with unified data management across Amazon S3 data lakes, Amazon Redshift data warehouses, operational databases, and enterprise applications.

·Data Processing:

o Use Visual ETL jobs and unified notebooks to perform data analysis, preparation, and integration with data sources like Amazon S3, Redshift, and AWS RDS.

·Orchestration and Automation:

o Create and manage SageMaker Pipelines and Workflows to automate the ETL Pipelines, ML model continuous integration and continuous delivery (CI/CD) lifecycle.

·Data Governance and Collaboration:

o Work within collaborative projects in SageMaker Unified Studio, leveraging the SageMaker Catalog (built on Amazon DataZone) to securely share data and AI artifacts.

o Implement various features in the project like Lineage, Data Quality, Metadata forms, Business Glossaries etc.

AI/ML:

·End-to-End MLOps:

o Build, deploy, execute, and monitor complete data and AI workflows using SageMaker Unified Studio's integrated environment.

·Model Development:

o Develop, train, and evaluate ML and generative AI models using SageMaker's purpose-built tools and algorithms.

o Utilize advanced features such as HyperPod for distributed training, JumpStart for pre-trained models, and SageMaker Experiments for tracking model versions.

·Generative AI Development:

o Rapidly build and customize generative AI applications within the integrated Amazon Bedrock environment in Unified Studio.

o Implement advanced customization capabilities like Knowledge Bases, Guardrails, Agents, and Flows.

·Security and Compliance:

o Implement and maintain security best practices, including fine-grained access controls and data protection, within the SageMaker environment.

·Performance Optimization:

o Optimize the performance and cost of ML workloads by right-sizing compute resources and monitoring job metrics.

·Troubleshooting:

o Utilize Amazon Q Developer's generative AI-powered assistance for code generation and resolving issues within the notebooks and jobs.

Required Skills:

• Experience with data processing and analytics using services integrated with Sagemaker Unified Studio (e.g., AWS Glue, Amazon EMR, Amazon Athena, AWS Redshift).
• Demonstrable expertise with Amazon SageMaker Unified Studio and its core components (Domain Units, Projects, Data Assets, Jobs, Data Products).
• Proficiency in PySpark, Python and relevant ML/AI libraries such as TensorFlow, PyTorch, and Scikit-learn.
• Experience with generative AI application development using Amazon Bedrock services within Unified Studio.
• Proven experience developing machine learning models and data pipelines on AWS.
• Solid understanding of MLOps principles and experience building CI/CD pipelines for ML models.
• Familiarity with AWS security best practices, including IAM roles, policies, and data governance, AWS Lake Formation
• Knowledge of SQL and experience with the built-in SQL editor in Unified Studio for data querying
• AWS Certified Data Engineer Associate / AWS Certified Machine Learning – Specialty or other relevant AWS certifications.

Required Technical/ Functional Competencies

Domain/ Industry Knowledge: 

• Basic knowledge of customer's business processes- relevant technology platform or product.
• Able to prepare process maps, workflows, business cases and simple business models in line with customer requirements with assistance from SME and apply industry standards/ practices in implementation with guidance from experienced team members.

Requirement Gathering and Analysis:

• Working knowledge of requirement management processes and requirement analysis processes, tools & methodologies.
• Able to analyse the impact of change requested/ enhancement/ defect fix and identify dependencies or interrelationships among requirements & transition requirements for engagement.

Product/ Technology Knowledge:

• Working knowledge of technology product/platform standards and specifications.
• Able to implement code or configure/customize products and provide inputs in design and architecture adhering to industry standards/ practices in implementation.
• Analyze various frameworks/tools, review the code and provide feedback on improvement opportunities.

Architecture tools and frameworks:

• Working knowledge of architecture Industry tools & frameworks.
• Able to identify pros/ cons of available tools & frameworks in market and use those as per Customer requirement and explore new tools/ framework for implementation.

Architecture concepts and principles:

• Working knowledge of architectural elements, SDLC, methodologies.
• Able to provides architectural design/ documentation at an application or function capability level and implement architectural patterns in solution & engagements and communicates architecture direction to the business.

Analytics Solution Design:

• Knowledge of statistical & machine learning techniques like classification, linear regression modelling, clustering & decision trees.
• Able to identify the cause of errors and their potential solutions.

Tools & Platform Knowledge:

• Familiar with wide range of mainstream commercial & open-source data science/analytics software tools, their constraints, advantages, disadvantages, and areas of application.

Required Behavioral Competencies

Accountability:

• Takes responsibility for and ensures accuracy of own work, as well as the work and deadlines of the team.

Collaboration:

• Shares information within team, participates in team activities, asks questions to understand other points of view.

Agility:

• Demonstrates readiness for change, asking questions and determining how changes could impact own work.

Customer Focus:

• Identifies trends and patterns emerging from customer preferences and works towards customizing/ refining existing services to exceed customer needs and expectations.

Communication:

• Targets communications for the appropriate audience, clearly articulating and presenting his/her position or decision.

Drives Results:

• Sets realistic stretch goals for self & others to achieve and exceed defined goals/targets.

Resolves Conflict:

• Displays sensitivity in interactions and strives to understand others’ views and concerns.

Certifications

Mandatory

 

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

Experience Level

Senior Level