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Types d'emploi
Work Style
Description et exigences
- Technical Excellence: Utilize strong technical skills to understand and interpret business requirements, translating them into effective data solutions.
- Complex Problem Solving: Demonstrate expertise in breaking down complex data sets and ambiguous problems, enabling clear communication of intricate analyses or findings to leadership and stakeholders.
- Effective Communication: Employ exceptional interpersonal skills to lead, motivate, and influence team members, fostering productive working relationships across various organizational levels.
- Organizational Efficiency: Exhibit excellent organizational abilities to prioritize tasks, negotiate effectively, and plan and coordinate activities. Consistently deliver desired outcomes with minimal supervision.
- Communication Excellence: Demonstrate exceptional written and verbal communication skills, facilitating clear and concise articulation of complex technical concepts and findings to diverse audiences.
Technical Abilities
- Proficiency in SQL and Python
- Strong understanding of relational databases
- Familiarity with Extract, Transform, Load (ETL) processes and tools for data movement between systems
- Experience in data integration and data modeling
- Demonstrated ability to create compelling and concise data visualizations using tools such as Tableau, Looker, Domo, or Microsoft PowerBI
- Hands-on experience with Google Cloud Platform, particularly BigQuery
- Familiarity with Infrastructure as Code (IaC) technologies like Pulumi or Terraform
- Experience with version control systems, specifically GitHub
- Experience with Apache Hadoop and Apache Spark for distributed processing of large datasets
- Familiarity with workflow management tools like Apache Airflow and Apache NiFi
Description supplémentaire du poste
- Requirement Gathering: Collaborate with stakeholders to understand needs and identify required datasets.
- Scope Definition: Collaborate with stakeholders to define project scope and objectives, ensuring alignment with data requirements.
- Data Acquisition: Procure datasets from diverse sources while ensuring data quality and integrity.
- Translation of Requirements: Translate stakeholder requirements into code, ensuring adherence to project goals
- Proof of Concept Development: Create prototypes for dashboards and reporting to validate ideas.
- Data Centralization: Centralize data from disparate sources into a unified repository or data warehouse for streamlined access and analysis.
- Frontend Visualization: Design and implement user-friendly dashboards and visualizations for effective data presentation.
- Reporting Cadence Establishment: Establish regular reporting schedules and workflows to deliver insights to stakeholders in a timely manner.
- Maintenance and Updates: Take ownership of maintaining and updating data pipelines, dashboards, and other data-related assets to ensure accuracy and relevance over time
- Cross-functional Collaboration: Collaborate with various teams across the organization to leverage data-driven insights and optimize operational efficiency.
- Support for Ongoing Initiatives: Provide data engineering support and expertise to Senior Systems Analyst and other team members on ongoing initiatives and projects.
- Ad Hoc Data Analysis: Assist stakeholders with ad hoc data analysis to facilitate decision-making and problem-solving processes.
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