Technical project manager

3 weeks ago

Bangalore City, India C5i Full time

Technical Understanding of Data Engineering Data Pipeline Architecture: Knowledge of data pipelines (ETL/ELT) and how data moves from source to destination. Cloud Platforms: Familiarity with platforms like AWS, Azure, or Google Cloud for data storage, processing, and analytics. Databases & Querying: Understanding different types of databases (SQL, No SQL) and data storage systems (e. G., Data Lakes, Warehouses). Big Data Frameworks: Experience with big data technologies such as Hadoop, Spark, or Kafka. APIs & Integrations: Understanding how APIs and various data integrations work between systems. Data Security & Compliance: Awareness of regulations such as GDPR, HIPAA, and practices around data privacy and security. Project Management Expertise Agile & Scrum Methodologies: Familiarity with Agile frameworks, sprint planning, backlog grooming, and release management. Stakeholder Management: The ability to manage expectations of cross-functional teams (data scientists, data engineers, business leaders). Risk Management: Proactively identifying, assessing, and mitigating project risks related to timelines, resources, and dependencies. Budget & Resource Planning: Managing budgets, resource allocation, and timelines for efficient project delivery. Documentation & Reporting: Efficient tracking and documentation of project progress, challenges, and solutions, keeping stakeholders informed. Data Governance & Quality Management Data Governance Frameworks: Understanding data governance practices such as role definition (Data Owner, Custodian) and compliance mechanisms. Data Quality: Ensuring accuracy, consistency, and reliability of data, and managing processes for data validation and cleansing. Metadata Management: Knowledge of tools and practices to manage and document metadata across systems. Cross-functional Leadership Collaboration with Engineers: Strong ability to work closely with data engineers, architects, and developers, understanding their challenges and providing clear guidance. Business Understanding: Ability to translate business needs into technical specifications and ensure alignment with business objectives. Communication: Clear and effective communication skills for presenting updates, risks, and strategies to both technical and non-technical stakeholders. Analytical and Problem-Solving Skills Problem-Solving: The ability to quickly analyze issues within data flows, integrations, or processes and facilitate resolution. Decision-Making: Making informed decisions based on data-driven insights, balancing between technical constraints and business goals. KPIs and Metrics: Familiarity with key performance indicators for project success, including data processing speed, reliability, and accuracy. Tool Proficiency Project Management Tools: Proficiency in tools like Jira, Trello, or Asana for project tracking. Data Engineering Tools: Awareness of data tools like Apache Ni Fi, Talend, or Informatica for managing data flows. Version Control & CI/CD: Basic understanding of version control systems (e. G., Git) and Continuous Integration/Continuous Deployment pipelines. Adaptability and Continuous Learning Staying Updated: Ability to stay current with emerging trends in data engineering, cloud computing, and big data technologies. Adaptability: Flexibility to adjust project plans or technical approaches as new information or challenges arise.

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