Job Title

Company Introduction: We are a financial services company with vast amounts of data from various sources. We currently lack a centralized system for data analysis, which limits our ability to make data-driven decisions and generate meaningful business intelligence. The Challenge: Our data is siloed and inconsistent, making it nearly impossible to run comprehensive reports and analytics. We need to design and implement a robust data warehouse solution to consolidate our data, ensure its quality, and enable advanced analytics for our business teams. The lack of a proper data strategy is costing us valuable insights. Objective: The goal is to design, build, and implement a scalable data warehouse, including a reliable ETL (Extract, Transform, Load) process, to centralize our data and provide a foundation for business intelligence. Detailed Job Description & Responsibilities Core Tasks: Collaborate with business stakeholders to understand data requirements and design an optimal data warehouse schema. Develop and implement a secure and reliable ETL process to extract data from various sources (e.g., transactional databases, APIs), transform it, and load it into the data warehouse. Ensure data quality and consistency throughout the ETL pipeline. Establish a comprehensive data backup and recovery strategy for the data warehouse. Configure and optimize the data warehouse for high-speed querying and reporting. Provide a detailed support and maintenance plan for the ETL pipeline and data warehouse for the first three months. Document the entire data warehousing architecture, ETL processes, and data lineage. Required Skills & Qualifications Technical Expertise: Proven experience in designing and implementing data warehouse solutions (e.g., using Snowflake, Redshift, BigQuery). Expertise in ETL/ELT tools and processes (e.g., Talend, Informatica, custom Python scripts). Strong SQL skills and knowledge of dimensional modeling (Star Schema, Snowflake Schema). Experience with cloud platforms (e.g., AWS, GCP, Azure). Proficiency in scripting languages like Python for data manipulation and automation. Soft Skills Excellent analytical and conceptual thinking skills to translate business needs into a technical solution. Strong communication skills to work with both technical and non-technical teams. Meticulous attention to detail for data quality and consistency. A documented data warehouse design and schema. A functional ETL pipeline with documentation. A comprehensive data quality and backup plan. A final report with a roadmap for future data warehousing and business intelligence initiatives. How to Apply Instructions: Submit a proposal outlining your experience with data warehousing and ETL. Provide a portfolio or examples of previous projects. State your hourly rate for this engagement. Skills Technical: Data Warehousing, ETL, Snowflake, Redshift, BigQuery, SQL, Dimensional Modeling, Python, Data Quality, Backup. Soft: Analytical skills, Communication, Problem-solving, Attention to detail. Additional Skills Data warehousing for specific industries Tags Data warehousing for specific industries Data backup and recovery best practices Database migration tools and technologies Compliance with database security regulations Business overview #J-18808-Ljbffr