What are the responsibilities and job description for the Data Environment Architect position at Parks Management Company Llc?
Job Responsibilities:
Data Lake Development:
- Design and implement a scalable data lake architecture.
- Define data ingestion processes and ensure data quality and integrity.
- Collaborate with stakeholders to understand data requirements and ensure alignment with business goals.
Business Intelligence Tools:
- Evaluate and implement business intelligence (BI) tools to enable data visualization and reporting.
- Develop dashboards and reports to provide actionable insights for decision-making.
- Train end-users on BI tools and best practices for data utilization.
Data Migration:
- Develop a comprehensive data migration strategy to transition legacy systems to the new data environment.
- Coordinate with IT and business teams to ensure seamless data transfer with minimal disruption.
- Monitor and troubleshoot migration processes to ensure data accuracy and consistency.
Collaboration and Stakeholder Engagement:
- Work closely with cross-functional teams to gather requirements and provide updates on project progress.
- Act as a liaison between technical teams and business units to ensure alignment on data initiatives.
Best Practices and Governance:
- Establish data governance policies and best practices to ensure data security and compliance.
- Stay current with industry trends and technologies to recommend improvements and innovations.
Job Qualifications:
- Bachelors degree in Computer Science, Data Science, Information Systems, or a related field.
- 5 years of experience in data architecture, data engineering, or a related role.
- Proven experience with data lake technologies (e.g., AWS S3, Azure Data Lake) and BI tools (e.g., Tableau, Power BI).
- Strong understanding of data modeling, ETL processes, and data governance.
- Experience in the automotive industry is a plus.
- Excellent communication skills and ability to work collaboratively with diverse teams.
Preferred Skills:
- Familiarity with cloud platforms (AWS, Azure, Google Cloud).
- Knowledge of programming languages (e.g., Python, SQL).
- Experience with data visualization and reporting tools.