Essential Responsibilities and Duties:

• Owns, develops and publishes enterprise MDM data model
• Aligns technical architecture framework with requirements defined by the Delivery team
• Provides leadership and guidance with MDM/DQ best practices, governance, standards and conventions
• Partners with security resources to ensure compliance with data security and privacy mandates
• Manages MDM and Databricks deployment lifecycle
• Design and implement scalable and reliable data pipelines for machine learning using Apache Spark, Delta Lake, MLflow, and other Databricks services
• Evaluates and recommends new and emerging MDM/DQ technologies, methodologies and standards
• Ensures consistency and compatibility with all other system technology components
• Mentors MDM Modelers and leads data modeling/quality efforts
• Conducts technical design reviews

Education:

• Bachelor’s degree in Engineering, Computer/Data Science or equivalent experience.

Responsibilities:

• Defines the MDM data model and architecture
• Utilizes a data modeling tool to develop "blueprints" for the Conceptual Data Model of the MDM architecture
• Develops enterprise conceptual models to integrate master data from diverse data sources into conformed, high quality, and referentially sound enterprise master data model
• Establishes and governs master data modeling standards that includes naming standards, data quality indicators, data categorization, ETL attribute usage, data consistency and reuse
• Designs logical master data models using the data modeling tool for all layers in the MDM technical architecture framework
• Mitigates performance implications of various data modeling and architecture decisions at the logical and physical layer as related to ETL, ad hoc query access, and static reporting
• Reviews and validates master data models with stakeholders and subject matter experts
• Collaborates with the Integration pillar to develop master data acquisition strategies and enterprise ETL design patterns aligned with the enterprise master data models
• Collaborates with database administrators to design and implement physical master data models including performance and quality controls such as indexing strategies, referential integrity constraints, versioning, release management and partitioning
• Resolves complex technical issues as they relate to master data architecture, performance, and various tools, working closely with other technical team members
• Creates master data and process flows to graphically depict the master data architecture component
• Provides technical leadership in evaluating, prototyping and evolving the MDM framework for emerging technologies related to enterprise analytics. These technologies may include unstructured "Big Data", data grids and cloud-based computing
• Effectively communicates MDM architecture and design details to team members, including Delivery, Architecture, Integration Governance, Operations, Support and Services and other stakeholders.

EXPERIENCE:

• 6 - 10 years of hands-on experience in Data Management / Development
• 5 years of experience in data modeling using CA Erwin or Embarcadero ER Studio
• 5 years of experience in data warehousing required
• 2 years as a technical lead
• 2 years of working experience with an MDM solution
• Experience implementing a Data Vault architecture preferred
• Working understanding of Tableau or similar in memory analysis tool
• Experience with Agile development methodologies and concepts required
• Experience with the following disciplines is required: Data Warehousing, EAI, Metadata Management, MDM, Data Quality Management, Relational Databases, Dimensional Databases, Semantics, Data Lifecycle Management, SQL, PL/SQL, UML, XML
• Proficient in Python, Scala, SQL, and other programming languages
• Experience with cloud platforms such as AWS, Azure, or GCP
• Experience with Databricks or similar platforms for machine learning
• Knowledge of machine learning concepts, techniques, and best practices
• Familiarity with DevOps tools and processes such as Git, CI/CD, Docker, Kubernetes, etc.
• Common Buy-Side MDM product data implementation experience and familiarity with procedures utilized to carry out Business Systems
• Excellent written communication and meeting facilitation skills required

Key Competencies Upon entry, intermediate level of understanding in:

• Data requirements
• Data quality and compliance e.g. scorecard management
• Data management principles
• Business process management
• Data stewardship, strategy and governance
• Data factory capabilities
• Data warehousing and business intelligence support Mandatory Technologies Strong experience with Informatica MDM, Good experience with Informatica IDQ Developer Technologies preferred Good experience with Informatica IDQ Analyst Experience with Oracle Experience with Unix or Linux Scripting Exposure to SSIS, MDS, JAMS, and Rundeck/ Control M

Behavior:

• Organized analytical thinker
• Conscious of data quality
• Good communication skills
• Good teaming skills
• Creative and innovative

About Regal Rexnord

Regal Rexnord Corporation (“Regal Rexnord”) is a leading manufacturer of electric motors, electrical motion controls, power generation and mechanical power transmission products and sub-systems, serving customers around the world in the general industrial, consumer, commercial construction, food & beverage, and alternative energy end markets, among others. Regal Rexnord sells its products and solutions to OEMs, through distributors, and directly to end-users. Regal Rexnord is a $7.2B company with 36,000 associates globally.

You may not know it, but Regal Rexnord impacts your life every day. The company’s products enable the fans in HVAC systems that keep us comfortable; the power source that keeps smart buildings running; the agricultural and food service equipment that keeps us fed; and the conveyer systems that keep e-commerce flowing, to name a few of the applications where our products are used.

Regal Rexnord’s business purpose is to create a better tomorrow by energy-efficiently converting power into motion. This means creating innovative solutions while focusing on both customer needs and the company’s commitment to sustainability. The company’s industrial powertrain and automation solutions offerings are an important part of the company's growth strategy. The company’s strategy includes leveraging 80/20 to prioritize all activities, including product excellence, operational excellence and commercial excellence (i) driving organic sales growth through the introduction of innovative new products, with a particular focus on improving energy efficiency, (ii) establishing and maintaining new customers, as well as developing new opportunities with existing customers, (iii) participating in higher growth end markets and geographies, and (iv) identifying and consummating strategic, value creating acquisitions.