Data Engineering Advisor

Position :
Data Engineering Advisor

As a Data Engineering Advisor, you will be responsible for creating and supporting analytical data marts by developing data integration pipelines (ETL) sourcing from various databases and systems. You will develop programs using coding languages (e.g., Python, SQL, PROC SQL, R) and / or low-code environments (e.g., Palantir Foundry) to create analyses and applications for stakeholders across the organization. You will work on data architecture, data engineering solutions, and best practices for analyzing very large datasets.

Additionally, you will perform data mining activities to derive insights, work with cloud OLAP systems (e.g., Snowflake), and stay current on new and emerging data science, data engineering, and big data techniques.

• Manage and scale data pipelines from internal and external sources to support new product launches and improve data quality.
• Facilitate data engineering activities including acquisition, extraction, normalization, transformation, and management of large and complex data sets.
• Stay informed about emerging data engineering, big data, and data science techniques; contribute to best practices, standards, and guidelines.
• Collaborate with subject matter experts to design and develop front-end applications and supporting data models / pipelines.
• Provide governance and oversight of data assets, environments, and procedures; enforce data asset naming conventions.
• Build and maintain data pipelines using big data technologies and ETL processes.
• Develop and maintain data warehouse schemas and data models to ensure consistency and accuracy.
• Align technical and business strategies with changing business and technology drivers.
• Create advanced visualizations and tools to provide insights and drive decision-making.
• Identify and develop Data-as-a-Service opportunities to improve data availability and consumption.

• Bachelors Degree in Computer Science, Information Systems, Engineering, Statistics, Mathematics, or equivalent STEM major.
• Seven or more years of experience in processing large data sets and hands-on experience in data transformation, aggregation, and filtering.

• Certifications such as Palantir Foundry Data Engineer, Azure Data Engineer, Certified Data Management Professional, Snow Pro Advanced, etc.
• Experience building and maintaining APIs and ETL pipelines using tools like Python, SQL, Apache Airflow, Azure Data Factory, etc.
• Familiarity with platforms such as Palantir Foundry, Snowflake, SAP, Oracle.
• Understanding of cloud-based data storage and architecture.
• Proven ability to implement data validation, metadata management, and maintain data consistency across systems.
• Experience in the electric utility industry or infrastructure investment planning.
• Ability to collaborate with cross-functional teams including IT, engineering, planning, and business units to deliver tailored data solutions.