Technical Project Manager / 2

As a Technical Project Manager, you will lead the delivery of end-to-end ETL projects using AWS and Spark. You will be responsible for managing a cross-functional agile team, ensuring successful project execution, and communicating with stakeholders to meet business objectives. You will need a strong technical understanding of data engineering, cloud platforms, and the ETL lifecycle to make informed decisions and drive delivery at a fast pace.

Key Responsibilities
Project Leadership: Lead and manage multiple projects, ensuring successful delivery within time, budget, and scope.
Agile Methodology: Facilitate agile ceremonies (daily stand-ups, sprint planning, sprint reviews, retrospectives) to drive team alignment, productivity, and collaboration.
Stakeholder Management: Act as the primary point of contact for stakeholders, ensuring regular updates on project status, risks, and deliverables. Manage expectations and ensure alignment on business and technical requirements.
Technical Oversight: Collaborate with technical teams, understanding the intricacies of data pipeline design and architecture. Ensure the team adheres to best practices in AWS and Spark-based ETL development.
Risk Management: Identify project risks early and develop mitigation strategies. Monitor progress and remove any roadblocks to project success.
Team Collaboration: Work closely with data engineers, architects, and other stakeholders to design, build, and deploy scalable ETL solutions on AWS.
Continuous Improvement: Foster a culture of continuous improvement, ensuring the team constantly enhances processes, methodologies, and tools.
Quality Assurance: Ensure that the ETL processes are optimized for performance, scalability, and reliability, meeting high-quality standards.

Required Skills and Qualifications
Experience: 7+ years of project management experience, focusing on delivering data engineering and ETL projects using AWS and Spark.
Technical Expertise: Strong knowledge of AWS services (e.g., S3, EMR, Lambda, Glue, Redshift) and Apache Spark. Experience with data pipelines, ETL frameworks, and distributed data processing.
Agile Methodology: Solid understanding of agile frameworks (Scrum, Kanban) and hands-on experience leading agile teams.
Stakeholder Management: Proven ability to communicate effectively with technical and non-technical stakeholders, managing expectations and delivering successful outcomes.
Problem-Solving: Strong analytical and problem-solving skills, with the ability to think strategically and troubleshoot complex issues in ETL pipelines.
Leadership: Experience leading teams, mentoring, and guiding engineers through complex technical challenges while ensuring timely delivery of projects.
Certifications: PMP, Scrum Master, or other relevant certifications are a plus.

Preferred Qualifications
Experience with other data processing frameworks like Apache Flink or Hadoop or Glue.
Experience with monitoring, logging, and optimization tools in AWS.
Understanding of data warehousing concepts and tools (e.g., Amazon Redshift, Snowflake).