IT Sr. Data Architect, Commercial

ConocoPhillips•Houston, TX

About The Position

We are seeking a highly skilled and experienced IT Sr. Data Architect, Commercial to join our team. Reporting to the Supervisor, Commercial Data, this role will be responsible for leading the design and development of data as a product for a variety of Commercial use cases, in line with the company's data strategy. The primary objective of the role is to bring together foundational components of Commercial data ecosystems to provide solutions that improve the architecture, quality and fidelity of the data consumed by Commercial business processes and analytics use cases. This role will be instrumental in enhancing our current data capabilities. The IT Sr. Data Architect, Commercial will also lead strategic aspects of the Commercial data strategy and be responsible for the operational aspects of data management, especially regarding product development and decision-making. IT Sr. Data Architect, Commercial will be part of a team of data architects, data governance analyst and data engineers responsible for implementing Commercial data projects while ensuring a high level of data quality based on corporate and industry standards. The team will also be responsible for developing and enforcing standards for data management and implementing data technology solutions for structured and unstructured datasets as well as data catalogs and data lineage to enhance visibility and access to data for Commercial groups. As our Commercial organization is implementing new tech strategies and going through transformation, the IT Sr. Data Architect, Commercial will play a key role in providing input and influence in our journey towards a strategic data organization. This role also requires a strong and current technology focus, hands-on practical design & architecture experience, experience with integration and implementation digital/ cloud technology and excellent written and communications skills.

Requirements

Legally authorized to work in the United States
Bachelor's degree or higher in Computer Science, Engineering, Geoscience, Information Technology, Information Systems or foreign equivalent
10 or more years of experience implementing and supporting complex Data Management initiatives including Datalake and traditional Data Warehousing
7 or more years of hands on experience with Cloud Platforms and Data Lake implementation to enable Data Science and Analytics capability
7 or more years of experience in data architecture, and data management in an enterprise environment.
5 or more years of experience with database platforms such as Snowflake or Teradata with demonstrated strength in SQL, data modeling, ETL development, and data warehousing.
5 or more years of experience of modern cloud-based data platform technologies e.g., Snowflake, ADLS, Data Bricks

Nice To Haves

10 or more years of hands-on data architecture experience
10 or more years experience and proficiency in Data Management tools such as: SQL, SDE, JSON, XML, scripting languages such as Python
Big Data technology stack including NoSQL, Spark, Hive, Kafka, StreamSets, IICS, ADF etc.
5 or more years of commercial or energy industry experience
5 or more years Delta Lake experience with query optimization
5 or more years of experience with Spark and any of the following programming languages: Python, Scala, Java etc
5 or more years of experience designing and implementing data ingestion techniques for real-time and batch processes into cloud-based platforms
Expert level of knowledge in designing, scaling and implementing data lake platform.
Advanced level of knowledge of master data management, real-time streaming data and cloud technologies
Advanced level of knowledge of well data lifecycle from exploration through to development, drilling and completion, production and eventual abandonment or relinquishment
Advanced level of DevOps proficiency, including Agile development process, containers, and source code control systems
Intermediate level of knowledge of Data Management principles, processes and data lifecycle
Basic level of Understanding of Data Science and related technologies
Work across structured, semi-structured, and unstructured data, with strong technical experience in large distributed systems, data warehousing, data lake at scale
Ability to take ownership, engage, lead change, achieve results, adapt, solve problems, manage risk and drive tasks to completion
Ability to lead initiatives, multi-disciplinary project teams, and influence stakeholder buy-in
Participate in strategy and planning sessions and be recognized as a capable team member that delivers value
Demonstrated ability to deal with ambiguity and maintain effective performance under stressful and uncertain conditions
Excellent oral and written communication skills; proven ability to represent point of view and discuss technical information with the business users in business language
Team player, and self-driven individual who can multi-task, work independently under minimal supervision and deliver on commitments
Excellent analytical mind and proven problem-solving skills
Demonstrated leadership and people skills, with ability to engage at all levels of the organization
Confident in engaging all levels of the organization in communicating a data strategy
Ability to influence others and drive change around data standards and best practices
Delivers positive results through realistic planning to accomplish goals
Builds effective solutions based on available information and makes timely decisions that are safe and ethical

Responsibilities

Responsible for evaluating new Data Management capabilities and technologies to drive Commercial business results and innovation to propel Commercial organization’s Data and Digital strategies.
Accountable for building an integrated data foundation that connects cross-commodity data across the lifecycles of our Commercial assets to provide a 360-degree view of data to deliver insights and predictions.
Responsible for conducting a comprehensive evaluation of the current Commercial data landscape to identify potential gaps in data management capabilities and formulate a roadmap for enhancement.
Accountable for the operationalization of new Data Management capabilities and tools and ensuring seamless integration with existing or new Commercial systems and processes (e.g. security, scalability, performance, reliability, FinOps, recovery etc.)
Responsible for creating blueprints that tie together our Commercial business processes and workflows with data in a cohesive way that strengthens our capabilities, accelerates delivery, and promotes innovation.
Develop and evaluate design options to ingest and catalogue real-time, structured, and unstructured data sets into Data Management environment per Commercial business priorities and use cases.
Provide input and influence teams focused on the data modernization and next generation data capabilities.
Cultivate relationships with peer Data Management groups and Enterprise Architects to ensure alignment, compliance and long-term sustainability of our Commercial digital assets
Build and maintain reference architecture, design patterns, decision matrices, common Information model and frameworks that drive Commercial operational efficiencies.
Participate in enterprise governance meetings to identify cross-functional synergies and assess potential risks.
Participates in risk review process to ensure Commercial data projects align with the organization's risk management and architecture standards.
Ensure consistency of Commercial data systems, tools, and architectural best practices across the organization, driving adoption across our teams and systems.
Proactively identify opportunities for automation and continuous improvements
Stays current with the latest trends, technologies, and best practices in data management, governance, and architecture.
Participate and support Agile quarterly planning for the team.
Collaborate with enterprise and Commercial teams to ensure alignment between Commercial data architecture and overall IT and business strategies.
Ensure consistency of Commercial data systems, tools, and architectural best practices, driving adoption across our Commercial teams and systems.
Expertise in optimizing queries and performance by establishing standards to minimize system workload and costs.