Data Architect–Apptio

Key Skills

Aartificial intelligence, Analytical and Problem solving, Apache Hadoop, AWS, Azure, Big Data Technology, Continuous Integration & Continuous Delivery - CI/CD, Data Architecture, Data Catalog, DevOps, Effective communication skills, ETL/ELT technologies, Google Cloud Platform (GCP), Java Programming, Machine learning techniques, Management, Metadata, NoSQL, PowerBI, Python Programming, Scala Programming, Scrum Agile Methodology, SPARK Programming, SQL, Tableau

Job Description

Your Role and Responsibilities

The Data Platform Architect is responsible for the end-to-end design, implementation, and management of data platforms that support Apptio’s data-driven initiatives. Their ownership areas and delivery responsibilities encompass data strategy, architecture, integration, security, governance, performance optimization, collaboration, documentation, monitoring, support, and scalability. Key outputs include alignment of the data platform architecture, platform design, data modeling, data integration design, standards documentation, architecture to support partner solutions, and performance aligned with the overall goals and objectives for Apptio’s business and vision.

Required Technical and Professional Expertise

• Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or a related field.
• At least 8 years of experience in a data architect role with a demonstrated track record of developing large-scale data solutions.
• Strong knowledge of various database technologies (SQL, NoSQL), data integration (ETL/ELT application integration) frameworks, and cloud services (AWS, Azure, GCP).
• Experience with big data technologies (Hadoop, Spark) and data streaming services (Kafka).
• Proficient in at least one programming language (Python, Java, Scala).
• Expertise in data modeling and data warehousing principles including an understanding of transactional schema, normalization/denormalization, star schema, snowflake schema, etc.
• Solid understanding of data security and privacy laws and regulations.
• Excellent communication and collaboration skills, with the ability to translate complex technical concepts into clear and actionable guidance for various stakeholders.

Preferred Technical and Professional Expertise

• Experience in AI and machine learning model deployment.
• Familiarity with DevOps practices and CI/CD processes.
• Prior experience in an Agile/Scrum development environment.
• Knowledge of metadata management, data catalog, reporting/BI, visualization tools, and dashboards (Tableau, PowerBI).
• Experience embedding or integrating third-party integration, metadata management, and reporting/BI platforms into other platforms or applications.
• Strong problem-solving abilities and analytical skills.
• Professional certifications related to data architecture (e.g., TOGAF, AWS Certified Solutions Architect) are a plus.