DBU - Data Architect

GPP Database Link 

Job Summary:

Expert in architecture and design of data analytics platform. Effectively and efficiently process, store and make data available to analysts and other consumers. Works with key business stakeholders, IT experts and subject-matter experts to plan, design and deliver optimal analytics and data science solutions. Manages a team of data engineers.

 

Key Responsibilities:

Gathers requirements and build roadmaps, architectures and lead decision making process for tools selection to help the Product Teams achieve their goals. Becomes a trusted partner, collaborates and aligns with the wider Organization and Enterprise Data Strategy. Creates data architectures for datalake, databases and data warehouses (i.e., designing and specifying the overall database/data warehouse structure based on functional and technical requirements). Creates and maintains optimal data pipeline architecture. Identifies, designs, and implements internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc. Works with stakeholders including the Executive, Product, Data and Design teams to assist with data-related technical issues and support their data infrastructure needs. Guarantees compliance with data governance and data security requirements while creating, improving and operationalizing these integrated and reusable data pipelines, enabling faster data access, integrated data reuse and vastly improved time-to-solution for the organization's data and analytics initiatives. Drives failure mode and troubleshooting methods across the entire flow of data within and across systems and acts as a strong advocate for a culture of process and data quality across development teams. Enables critical business decision making at the executive level via delivery of data from many source systems across the organization. Works with data and analytics experts to strive for greater functionality in our data systems. Coaches and develops less experienced team members. Develop strong relationships to deliver business value using relevant Business Relationship Management practices.

Competencies: 
Collaborates - Building partnerships and working collaboratively with others to meet shared objectives.

Communicates effectively - Developing and delivering multi-mode communications that convey a clear understanding of the unique needs of different audiences.

Customer focus - Building strong customer relationships and delivering customer-centric solutions.

Decision quality - Making good and timely decisions that keep the organization moving forward.

Manages ambiguity - Operating effectively, even when things are not certain or the way forward is not clear.

Manages complexity - Making sense of complex, high quantity, and sometimes contradictory information to effectively solve problems.

Tech savvy - Anticipating and adopting innovations in business-building digital and technology applications.

Quality Assurance Metrics - Applies the science of measurement to assess whether a solution meets its intended outcomes using the IT Operating Model (ITOM), including the SDLC standards, tools, metrics and key performance indicators, to deliver a quality product.

Solution Design - Creates and defines the solution design complete with instrumentation and measurement, using industry standards and tools, version control, and build and test automation to synthesize diagrams, models and documentation in order to build a solution that meets buildability, business, technical, security, governance and compliance requirements.

System Solution Architecture - Creates solution designs and patterns using the Cummins Technical Reference Model (CTRM), CLEAN standards, and existing reference patterns to maintain alignment to Cummins standards.

Data Quality - Identifies, understands and corrects flaws in data that supports effective information governance across operational business processes and decision making.

Problem Solving - Solves problems and may mentor others on effective problem solving by using a systematic analysis process by leveraging industry standard methodologies to create problem traceability and protect the customer; determines the assignable cause; implements robust, data-based solutions; identifies the systemic root causes and ensures actions to prevent problem reoccurrence are implemented.

Values differences - Recognizing the value that different perspectives and cultures bring to an organization. 

Education, Licenses, Certifications: 
College, university, or equivalent degree in relevant technical discipline, or relevant equivalent experience required. This position may require licensing for compliance with export controls or sanctions regulations. 

Experience: 
 

-10-15 years of experience 

- Significant experience in a relevant discipline area is required. Knowledge of the latest technologies and trends in data engineering are highly preferred and includes:
- Analyzing complex business systems, industry requirements, and/or data regulations
- A strong background in processing and managing large data sets
- Proven Architecture and design experience in Big Data open source tools including but not limited to Java, Map-Reduce, SPARK, HBase, Hive, Kafka, ODBC and SQL query language
- Proven design and development experience in clustered compute cloud-based implementation experience
- Experience developing applications requiring large file movement for a Cloud-based environment and other data extraction tools and methods from a variety of sources
- Experience in building analytical solutions
- Experience in databases and data management
Significant experiences in the following are preferred:
- Experience with IoT technology 
- Experience in Agile software development

1) Work closely with business Product Owner to understand product vision.
2) Accountable for conducting comprehensive analyses to identify deficiencies in the current data architecture and redesigning the data framework to optimize the overall DBU Data & Analytics.
3) Play a key role across DBU Data & Analytics Power Cells to define, develop data architecture and strategy.
4) Closely partner with CMI Enterprise Data Architecture, AAI Solutions Architecture to align DBU projects data design and modeling standards.
5) Play the role of Federated Data Architect and represent DBU Data & Analytics projects in CMI Architecture forums.
6) Independently design, develop Conceptual, Logical and Physical Data Models for the DBU Data & Analytics projects.
7) Responsible for defining the data architecture strategy, execution of critical programs like Quantum, Unified Data Model, BI Simplification, Product Lifecycle Management, Customer + Product data quality and governance.
8) Create, maintain, and manage the data architecture documentation for DBU Data & Analytics. 
9) Own and document governance processes related to data architecture
10) Take part in evaluation of new data tools, POCs and provide suggestions.
11) Own developed data models and provide support for enhancements, performance optimization, and issue resolution to ensure data accuracy and usability.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Preferred SkillsStrong SQL skillsExpertise in Dimensional ModelingWorking knowledge of at least one data platform (Snowflake, Databricks Delta Lake)Understanding of Big DataExpertise in RDBMSProfessional certifications in Data ArchitectureSAP working experience preferred

 

Cummins is an equal opportunity employer. Our policy is to provide equal employment opportunities to all qualified persons without regard to race, sex, color, disability, national origin, age, religion, union affiliation, sexual orientation, veteran status, citizenship, gender identity, or other status protected by law.