Required Skills: AWS cloud, PySpark, SQL, DevOps

Job Description

• Design and implement scalable data architectures on AWS cloud platforms.
• Develop and optimize data pipelines using PySpark for large-scale data processing.
• Proven experience in data architecture and cloud-based solutions, especially AWS.
• Bachelor’s degree in data management, computer science, information systems, mathematics, data/analytics or a related field preferred or equivalent work experience
• At least 3-4 years of work experience in data management disciplines including data integration, data modeling, solutions architecture, optimization and data quality
• Knowledge of business systems and processes and their impact on data and analytics objectives
• Ability to assess rapidly changing technologies and apply them to business needs
• Business domain, data/content and process understanding
• Understanding of the Business Intelligence, Data Engineering and Data Science and Data Governance processes and platforms
• Thorough knowledge of relational and non-relational database theory and structured query language (SQL)
• Understanding of common data architecture frameworks
• Understanding of metadata models, taxonomies and ontologies, as well as of the challenges of applying structured techniques (data modeling) to less-structured sources
• Skilled working across multiple deployment environments including cloud, on-premises and hybrid
• Adept at applying software engineering methodologies and DevOps principles to data architectures and platforms to improve the communication, integration, reuse and automation of data flows across the organization
• Exceptional analytical, quantitative and logical problem-solving abilities
• Must be highly creative, collaborative, and able to communicate effectively with IT and business
• Capacity to be productive when working independently or collaboratively
• Ability to effectively manage time to handle competing high priority projects

• Significant experience in successfully launching, planning, executing data architecture projects
• Strong employee development skills, which include onboarding, mentoring, and coaching staff
• Ability to analyze project, program and portfolio needs, as well as determine the resources needed to achieve objectives and overcome cross-functional barriers
• Proven ability to establish the strategic direction of a team and manage analytics projects
• Persuasive with excellent interpersonal skills and the ability to interact effectively with others, including team members and senior management
• Skilled in all areas of analytics personnel management, particularly employee selection, training, performance evaluation and salary development