What are the responsibilities and job description for the Data Modeler / Data Architect – Production Optimization position at Cadre Technologies Services LLC?
Job Title : Data Modeler / Data Architect Production Optimization
Location : Spring, TX - 77389
Job Type : 12 Months (Long Term Contract)
Job Role Summary :
Client's Upstream Data Office has a mission to develop Upstream enterprise data products in support of the Upstream business strategies to treat data as an asset to maximize business value. The Data Architect will work closely with other Data Architects, IT Platform Architects, subject matter experts (SMEs), data engineers and developers to contribute to the design of data products and consult with Upstream projects to ensure data architecture is aligned with enterprise data principles and standards. The data architect will work with business contacts in the Product Optimization team and focus on data within this domain.
Job Requirements :
Master's or Bachelor's degree in business, computer science, engineering, systems analysis or a related field
Minimum 3 years of experience in data design / architecture and strong willingness to continue learning
Minimum 3 years of experience in Upstream Oil and Gas Production Optimization, Production Volumes, and Production Revenue Accounting
Recent experience developing reference data architecture, data modeling (conceptual, logical,physical,and Type 2 Dimensional Modelling), data profiling, data quality analysis, building business data glossaries and data catalogs
Knowledge regarding data governance and master / reference data management programs
Experience using Snowflake, SQL query language and E / R Studio data modeling tool
Able to design solutions around Role-Based Access (RBA)
Experience working with agile delivery teams
Effective planning, communication, collaboration and persuasion skills to drive needed change across the company
Expert written and verbal communication skills; familiarity with SharePoint team sites to collaborate; self-starter, takes initiative and is able to work in a fast-paced environment
Preferred Skills & Experience :
Experience and knowledge of Upstream Oil & Gas Production Optimization, Production Volumes, and Production Revenue Accounting - business processes and business terms
Experience with tools such as TAMR, Collibra, and ER Studio
Understanding of large data store technologies (Data Lakes, Data Warehouse, Data Hubs, etc.) Specifically Snowflake
Experience with Type 2 Dimensional Modelling
Knowledge of JSON, Python, GIT; understanding of API concepts and integration architecture
Knowledge of TOGAF Framework and DAMA DMBoK v.2 desirable
Knowledge and experience working with Role-based access
Leadership : Strong interpersonal skills with ability to influence without direct authority; able to effectively interact with large and diverse user community
Strong background in data, analytics, systems and tools : good working knowledge of OSDU, Graph, ADX, NoSQL and other modern data storage solutions and related data extraction tools
Familiarity with Upstream Data, common workflows, and data sources / repositories
Job Responsibilities :
The UDO Data Architect Production Optimization will work towards building and / or providing knowledge in support of the overall Upstream Data Office mission and data strategy. To achieve these goals, the Data Architect will be required to analyze current state data architectures and conceive desired future state data architectures and identify activities needed to close the gap to achieve the future state within Production Optimization. Some examples of these activities / deliverables are :
Develop and maintain UDO conceptual and logical data models, type 2 dimensional models, data flow diagrams, and conceptual data architecture designs in support of the Production Optimization Business Capability which include production volumes and production revenue accounting processes and terms.
Collaborate with Data and IT Architects in defining UDO architectural standards by developing UDO Architectural Decision Records (ADRs)
Provide data architectural and modeling support, guidance, and mentorship to data engineering product teams to ensure they can successfully deliver, support, and where applicable standardize data products
Partner with IT to ensure Upstream Data Foundation Data Platforms and related tooling satisfies UDO's business needs
Work with Data Governance teams to ensure business glossaries, data dictionaries and data catalogs are created and maintained
Drive strategies / approaches and principles for data management (including master / reference data and identification of key data domains, data governance framework, data integration, etc.)
Ensure data architecture of solutions delivered by data engineering teams support proper data security, retention, and classification and are aligned with existing data architectural standards, data models, and data flows
Partner with data product owners, data engineers, business SMEs, data stewards, data custodians, and data governance groups to support business data needs
Lead assessments of business / data requirements for Upstream projects to validate that overall design adheres to key data architecture standards and principles
As part of delivering data products, partner with Upstream Capability business SMEs, data stewards, and / or data custodians to design and contribute data models to industry standards organizations
Key Points :
1. Data Architects scope mostly involves data design activities specific to the development of data products (e.g., developing conceptual and logical data models, data flows, source / target mapping, identifying critical data elements, maintaining Upstream reference model / ontology etc.)
2. They do not make or drive technology or platform choices although they may provide an input into the decision-making process.
3. They should advocate / recommend a particular data modeling technique that best fits the data product use case (e.g., data and consumption suggest semi-structure noSQL data model is a better fit that dimensional data model or vice versa)
4. They do not design a system of records / applications and the integration between them and / or platforms.
5. They do not prioritize data product features and / or directly work with the business capabilities to identify business requirements. They do identify technical / data architectural requirements as in input to data product design.
6. They do drive standardization through mentoring, contributing to ADRs, sharing best practices, and validating solutions produced by data engineering teams align with existing Data Architecture standards
7. They can be an advocate for the data engineering teams to IT application and platform teams in ensuring that data tools and platforms satisfy business requirements
8. They can lead data architecture assessments of business and / or IT projects to ensure project solutions satisfy established data architecture standards
9. They can contribute to the OSDU Forum in the form of data definitions and / or data modeling to support the development of a UDF Data Product