Senior Manager, Data Platforms

Role Overview

• Interpret and deliver impactful strategic plans improving data integration, data quality, and data delivery in support of business initiatives and roadmaps.
• Design the structure and layout of data systems, including databases, warehouses, and lakes.
• Partner with data architecture to design systems that meet the organization's needs by defining data schemas, optimizing data storage, and establishing data access controls and security measures.
• Define and implement the long-term technology strategy and innovations roadmaps across analytics, data engineering, and data platforms.
• Design and implement processes for the ETL process from various sources into the organization's data systems.
• Translate high-level business requirements into data models and appropriate metadata, test data, and data quality standards.
• Manage senior business stakeholders to secure strong engagement and ensure that the delivery of the project aligns with longer-term strategic roadmaps.
• Simplify the existing data architecture, delivering reusable services and cost-saving opportunities in line with the policies and standards of the company.
• Lead and participate in the peer review and quality assurance of project architectural artifacts across the EA group through governance forums.
• Define and manage standards, guidelines, and processes to ensure data quality.
• Work with IT teams, business analysts, and data analytics teams to understand data consumers' needs and develop solutions.
• Evaluate and recommend emerging technologies for data management, storage, and analytics.

Requirements

• Bachelor's degree in computer science, Management Information Systems (MIS) or related degree preferred; or equivalent work experience
• Generally, 7+ years of experience in data modeling, database design, or related field
• Hands-on relational, dimensional, and analytical project experience using RDBMS, NoSQL data platform technologies, and ETL
• Strong ability in programming languages such as Java, Python, and C/C++
• Ability in data science languages/tools such as SQL, R, SAS, or Excel
• Proficiency in the design and implementation of modern data architectures and concepts such as cloud services (AWS, Azure, GCP), real-time data distribution (Kafka, Dataflow), and modern data warehouse tools (Snowflake, Databricks)
• Experience with database technologies
• Understanding of entity-relationship modeling, metadata systems, and data quality tools and techniques
• Ability to think strategically and relate architectural decisions and recommendations to business needs and client culture
• Ability to assess traditional and modern data architecture components based on business needs
• Experience with business intelligence tools and technologies such as ETL, Power BI, and Tableau
• Ability to regularly learn and adopt new technology, especially in the ML/AI realm
• Strong analytical and problem-solving skills
• Ability to synthesize and clearly communicate large volumes of complex information to senior management of various technical understandings
• Ability to collaborate and excel in complex, cross-functional teams involving data scientists, business analysts, and stakeholders
• Ability to guide solution design and architecture to meet business needs.

Tech Stack

• AWS
• Azure
• Cloud
• ETL
• Google Cloud Platform
• Java
• Kafka
• NoSQL
• Python
• RDBMS
• Realm
• SQL
• Tableau

Benefits

• Remote work options