Data Analysis Manager

2 weeks ago


Dubai, Dubai, United Arab Emirates Dicetek LLC Full time
Roles and responsibilities
  1. Understanding of Data Analytics:
  2. Familiarity with data lifecycle: collection, storage, processing, analysis, and visualization.
  3. Knowledge of advanced analytics techniques such as predictive modeling, machine learning, and AI.
  4. Big Data and Cloud Platforms:
  5. Experience with tools like Hadoop, Spark, or Snowflake.
  6. Understanding of cloud platforms such as AWS, Azure, or Google Cloud.
  7. Data Integration and ETL:
  8. Awareness of ETL processes and tools like Informatica, Talend, or Apache NiFi.
  9. Database Management:
  10. Proficiency in working with relational (SQL) and non-relational (NoSQL) databases.
  11. Data Visualization:
  12. Familiarity with tools like Tableau, Power BI, or Looker.
  13. Cybersecurity and Compliance:
  14. Awareness of data security, privacy regulations (e.g., GDPR, CCPA), and governance best practices.

Certifications (advantage to have)

  1. Project Management:
  2. PMP (Project Management Professional)
  3. Certified Scrum Master (CSM)
  4. PRINCE2
  5. Data and Analytics:
  6. Google Data Analytics Certification
  7. AWS Certified Data Analytics - Specialty
  8. Microsoft Certified: Azure Data Engineer Associate
  9. Business Analysis:
  10. CBAP (Certified Business Analysis Professional)
  11. PMI-PBA (Professional in Business Analysis)

Experience

  1. Domain Expertise: Experience in the industry relevant to the analytics platform (e.g., finance, healthcare, retail).
  2. Technical Project Delivery: Previous involvement in implementing analytics platforms or similar technical projects.
  3. Cross-functional Team Leadership: History of working with multi-disciplinary teams, including engineers, analysts, and business units.
  4. Define Project Scope : Work with stakeholders to define the project's objectives, deliverables, and expected outcomes, ensuring alignment with business goals.
  5. Data Strategy : Help shape the data strategy by advising on data collection, processing, and analytics methods.
  6. Develop Project Roadmap : Create detailed project timelines, milestones, and resource plans, ensuring that all project phases are accounted for and that progress is tracked.
  7. Risk Management : Identify and mitigate risks related to project scope, timeline, resources, or data quality that might impact project success.
Desired candidate profile
  1. Project Management Expertise
  2. Project Management Methodologies : Knowledge of project management methodologies such as Agile , Waterfall , or Scrum to manage and adapt projects effectively.
  3. Time Management : Strong ability to manage timelines, set priorities, and meet deadlines while handling multiple tasks and responsibilities.
  4. Task Delegation : Ability to delegate tasks effectively, ensuring that team members are empowered to perform their best work.
  1. Data and Analytics Knowledge
  2. Understanding of Data : Familiarity with data management practices, data quality, data governance, and data integration techniques.
  3. Advanced Analytics : Knowledge of machine learning, artificial intelligence, predictive modeling, and statistical analysis, although hands-on experience with coding is not typically required.
  4. Data Visualization : Proficiency with data visualization tools like Power BI , Tableau , or Looker to help present analytics results in an easily digestible format for stakeholders.
  1. Stakeholder Management and Communication
  2. Communication Skills : Strong verbal and written communication skills to clearly explain complex data insights and analytics results to non-technical stakeholders.
  3. Stakeholder Alignment : Ability to manage and align diverse stakeholders, including business leaders, technical teams, and end-users, with the project's goals and objectives.
  4. Influence and Negotiation : Skilled in influencing decisions and negotiating project scopes, timelines, and resources with stakeholders.
  1. Analytical and Problem-Solving Abilities
  2. Critical Thinking : Ability to think critically and problem-solve, especially in situations involving large or complex data sets and unforeseen challenges.
  3. Decision-Making : Ability to make data-driven decisions and use analytics tools to optimize outcomes and mitigate risks.
  4. Data-Driven Approach : Focus on ensuring that analytics are actionable, helping the organization make decisions based on accurate, real-time data.
  1. Leadership and Team Collaboration
  2. Team Leadership : Strong leadership skills to guide cross-functional teams, particularly in a fast-paced and often evolving environment.
  3. Motivating Teams : Ability to motivate and inspire teams, particularly data analysts, scientists, and engineers, to deliver high-quality results.
  4. Collaboration : Work collaboratively across departments and with different functional teams, balancing technical and business priorities.
  1. Change Management and Adaptability
  2. Agile Adaptability : Ability to adjust project plans quickly in response to changing business priorities, new data findings, or technology changes.
  3. Flexibility : Comfort in working in a constantly evolving technological and business environment, with the ability to pivot or adjust strategies when needed.
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