Key Responsibilities:Scrum Framework Implementation:Facilitate the adoption of Agile principles and practices.Act as a servant leader, ensuring the team's adherence to Scrum ceremonies and processes.Collaborate with Release Train Engineers (RTEs) and other Scrum Masters to ensure alignment across multiple teams.Agile Coaching:Coach and mentor teams, Product Owners, and stakeholders on agile and Scrum practices.Provide guidance on Scrum ceremonies, roles, and artifacts to ensure effective implementation.Facilitation:Lead and facilitate Scrum ceremonies, including Program Increment (PI) Planning, Inspect and Adapt (I&A), and Sprint Planning.Foster collaboration and communication among team members and stakeholders.Continuous Improvement: Identify and address impediments to the team's progress.Encourage a culture of continuous improvement, including retrospectives and feedback loops.Metrics and Reporting:Monitor and report on key agile metrics to track team performance and progress.Work with teams to identify areas for improvement based on metrics and feedback.Stakeholder Communication: Communicate effectively with stakeholders, keeping them informed of progress and impediments.Collaborate with Product Owners to ensure alignment between business objectives and team deliverables.Qualifications and Experience:Bachelors degree in computer science, Information Technology, or related field. (Mandatory)Certified Scrum Master (CSM) or PSM or any SAFe CertificationHands-on experience in Azure DevOps (ADO), Jira, Confluence, or similar platforms. (Mandatory) Proven experience as a Scrum Master, with a deep understanding of Scrum principles and Agile methodologies in a technical environment. (Mandatory)Strong understanding of software development life cycle (SDLC) and technical project management. (Mandatory).Experience in a technical role such as software development, or DevOps.Strong understanding of the SAFe framework and principles.Excellent communication, leadership, and problem-solving skills.Having prior experience in delivering data analytical projects and possessing a strong understanding of ETL, Azure Cloud, (CI/CD) pipelines and report fundamentals is highly advantageous for the Scrum Master.Advanced certifications (e.g., PMI-ACP, PMI-PMP is considered a strong advantage.Previous experience in agile transformations and scaling frameworks.Knowledge of other Agile frameworks such as Kanban, Lean, or XP.Strong analytical skills and ability to make data-driven decisions.Ability to work effectively in a fast-paced and dynamic environment.

Key Responsibilities:1. Design and implement scalable, high-performance data pipelines using AWS services2. Develop and optimize ETL processes using AWS Glue, EMR, and Lambda3. Build and maintain data lakes using S3 and Delta Lake4. Create and manage analytics solutions using Amazon Athena and Redshift5. Design and implement database solutions using Aurora, RDS, and DynamoDB6. Develop serverless workflows using AWS Step Functions7. Write efficient and maintainable code using Python/PySpark, and SQL/PostgrSQL8. Ensure data quality, security, and compliance with industry standards9. Collaborate with data scientists and analysts to support their data needs10. Optimize data architecture for performance and cost-efficiency11. Troubleshoot and resolve data pipeline and infrastructure issuesRequired Qualifications:1. bachelors degree in computer science, Information Technology, or related field2. Relevant years of experience as a Data Engineer, with at least 60% of experience focusing on AWS3. Strong proficiency in AWS data services: Glue, EMR, Lambda, Athena, Redshift, S34. Experience with data lake technologies, particularly Delta Lake5. Expertise in database systems: Aurora, RDS, DynamoDB, PostgreSQL6. Proficiency in Python and PySpark programming7. Strong SQL skills and experience with PostgreSQL8. Experience with AWS Step Functions for workflow orchestrationTechnical Skills:- AWS Services: Glue, EMR, Lambda, Athena, Redshift, S3, Aurora, RDS, DynamoDB, Step Functions- Big Data: Hadoop, Spark, Delta Lake- Programming: Python, PySpark- Databases: SQL, PostgreSQL, NoSQL- Data Warehousing and Analytics- ETL/ELT processes- Data Lake architectures- Version control: Git- Agile methodologies