Senior Data Technical Product Manager

Role Overview

• Demonstrating wide and deep knowledge in data engineering, data architecture, and data science.
• Ability to guide, lead, and work with the team to drive to the right solution.
• Engaging frequently (80%) with the development team; facilitate discussions, provide clarification, story acceptance and refinement, testing and validation; contribute to design activities and decisions; familiar with waterfall, Agile scrum framework.
• Owning and manage the backlog; continuously order and prioritize to ensure that 1-2 sprints/iterations of backlog are always ready.
• Collaborating with UX in design decisions, demonstrating deep understanding of technology stack and impact on final product.
• Conducting customer and stakeholder interviews and elaborate on personas.
• Demonstrating expert-level skill in problem decomposition and ability to navigate through ambiguity.
• Partnering with the Service Owner to ensure a healthy development process and clear tracking metric to form standard and trustworthy way of providing customer support.
• Designing and implementing scalable and robust data pipelines to collect, process, and store data from various sources.
• Developing and maintaining data warehouse and ETL (Extract, Transform, Load) processes for data integration and transformation.
• Optimizing and tuning the performance of data systems to ensure efficient data processing and analysis.
• Collaborating with product managers and analysts to understand data requirements and implement solutions for data modeling and analysis.
• Identifying and resolving data quality issues, ensuring data accuracy, consistency, and completeness.
• Implementing and maintaining data governance and security measures to protect sensitive data.
• Monitoring and troubleshoot data infrastructure, perform root cause analysis, and implement necessary fixes.

Requirements

• Have a Bachelor's or higher degree in Computer Science, Information Systems, or a related field.
• Have minimum 6-10 years of proven experience as a Data Engineer or similar role, working with large-scale data processing and storage systems.
• Have Proficiency in SQL and database management systems (e.g., MySQL, PostgreSQL, or Oracle).
• Have Extensive knowledge working with SAP systems, Tcode, data pipelines in SAP, Databricks related technologies.
• Have Experience with building complex jobs for building SCD type mappings using ETL tools like PySpark, Talend, Informatica, etc.
• Have Experience with data visualization and reporting tools (e.g., Tableau, Power BI).
• Have Strong problem-solving and analytical skills, with the ability to handle complex data challenges.
• Have Excellent communication and collaboration skills to work effectively in a team environment.
• Have Experience in data modeling, data warehousing, and ETL principles.
• Have familiarity with cloud platforms like AWS, Azure, or GCP, and their data services (e.g., S3, Redshift, BigQuery).
• Have advanced knowledge of distributed computing and parallel processing.
• Experience with real-time data processing and streaming technologies (e.g., Apache Kafka, Apache Flink).
• Knowledge of containerization and orchestration technologies (e.g., Docker, Kubernetes).
• Certification in relevant technologies or data engineering disciplines.
• Having working knowledge in Databricks, Dremio, and SAP is highly preferred.

Tech Stack

• Amazon Redshift
• Apache
• AWS
• Azure
• BigQuery
• Cloud
• Docker
• ETL
• Google Cloud Platform
• Informatica
• Kafka
• Kubernetes
• MySQL
• Oracle
• Postgres
• PySpark
• SQL
• Tableau

Benefits

• Contemporary work-life balance policies and wellbeing activities.