IT Sr. Data Engineer, Commercial

ConocoPhillips•Houston, TX

About The Position

We are seeking a highly skilled and experienced IT Sr. Data Engineer, Commercial to join our team. Reporting to the IT Supervisor, Commercial Data, this role will be responsible for building data pipelines from source systems and external data providers into the data management and analytics environments with validation to allow creation and operations of analytical solutions and Commercial models. The Commercial organization is going through transformation initiatives moving from ETRM-centric to data-centric architectural design and implementing new tech strategies including new ETRM systems. The initial focus of this role will be building/enhancing Commercial analytics data ingestion pipelines for Commercial models and supporting the Commercial Transformation initiatives. The IT Sr. Data Engineer, Commercial will be part of a team of data architects, a data governance analyst and data engineers responsible for implementing Commercial data pipelines 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. This role will work closely with Corporate IT operational support managed services team, database administrators, analytics architect, and IT infrastructure support to ensure system availability and timely issue resolution. This role will be proficient at integrating and preparing large, varied datasets including time series data and designing specialized database tables and information links within the environment. The person will work closely with Commercial data/quant analysts, data scientists, model owners, project/program managers, data architects, and the data governance analyst to provide clean and reliable data. This role requires a strong and current technology focus, practical analytical experience, and excellent written and communications skills.

Requirements

Legally authorized to work in the United States
Bachelor's degree or higher in Computer Science, Math, Engineering, Statistics, Information Systems, Information Science, or related fields
10 or more years of hands-on experience in designing, scaling and implementing data pipelines for structured and non-structured data into cloud-based data platforms
10 or more years of experience in data engineering in an enterprise environment with demonstrated strength in SQL, data modeling, ETL development, and data warehousing
10 or more years of Experience with an RDBMS (Oracle, PostgreSQL)
7 or more years of experience with practical programming skills including advanced knowledge of Python
5 or more years of experience of modern cloud-based data platform technologies e.g., Snowflake, ADLS, Data Bricks
5 or more years of experience with data visualization/analytics tools (Spotfire, Power BI, Sigma) advanced Excel skills

Nice To Haves

MS Degree in Computer Science, Math, Engineering, Statistics, Information Systems, Information Science, or related fields
5 or more years of Energy industry and Commercial experience
5 or more years of Experience with Cloud DevOps (Azure, AWS Cloud Formation Terraform) and Infrastructure as Code (IaC)
Experience with handling Commercial operational and trading analytics data
Experience with data engineering and data analytics tool set such as Airflow, Streamlit, UiPath, Document AI, etc.
Hands on experience and proficiency in Data Management tools – SQL, SDE, JSON, XML, scripting languages such as Python
Big Data technology stack including NoSQL, Spark, Hive, Kafka, StreamSets, IICS, ADF etc.
Intermediate level of knowledge one or more programming languages (R, C++, Java, Perl, Spark)
Work across structured, semi-structured, and unstructured data, with strong technical experience in large distributed systems, data warehousing, data lake at scale
Comprehensive knowledge of Data Management principles, processes and data lifecycle
Advanced knowledge of master data management, real-time streaming data and cloud technologies
Understanding of Data Science and related technologies
Excellent verbal and written presentation skills, with the ability to communicate clearly and persuasively
An understanding of project processes and methodology to support project management initiatives and delivery
Team player, and self-driven individual who can multi-task, work independently under minimal supervision and deliver on commitments
Open attitude towards and ability to learn and utilize new technologies and standards
Ability to take ownership, engage, lead change, achieve results, adapt, solve problems, manage risk and drive tasks to completion
Demonstrated ability to deal with ambiguity and maintain effective performance under stressful and uncertain conditions
Excellent analytical mind and proven problem-solving skills
Project Management skills
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

Design and develop robust data pipelines, ETL/ELT processes, and workflow orchestration systems to automate data ingestion, transformation, and distribution across multiple platforms for Commercial
Build and maintain scalable data infrastructure including data warehouses, data lakes, and streaming systems that support high-volume data processing and analytics workloads
Implement data quality validation, monitoring frameworks, and error handling mechanisms to ensure reliable data delivery and maintain system performance standards
Collaborate with data architects and analysts to translate business requirements into technical specifications for data processing solutions and system enhancements
Optimize data processing performance through query tuning, indexing strategies, and resource management to support efficient analytics and operational reporting
Establish data security protocols, access controls, and backup procedures to protect sensitive information and ensure business continuity for critical data systems
Monitor system health, troubleshoot data pipeline failures, and implement automated recovery procedures to maintain operational reliability and minimize downtime
Collaborate with business subject matter experts and data scientists to create datasets and engineer features for analytical models
Monitor Commercial trading analytics models performance
Adhere to ConocoPhillips’ governance and compliance policies for data and processes
Collaborate with Data Architect to develop and evaluate design options to ingest and catalogue real-time, structured, and unstructured datasets into Data Management environments per Commercial business priorities and use cases
Cultivate relationships with peer Data Management groups to ensure alignment, compliance and long-term sustainability of our Commercial digital assets
Proactively identify opportunities for automation and continuous improvements
Stays current with the latest trends, technologies, and best practices in data management and data engineering
Participate in and support Agile quarterly planning for the team.
Expertise in optimizing queries and performance by establishing standards to minimize system workload and costs