Data Engineer en Bakerhughes

Data Engineer

As a Data Engineer, you will be part of the Data & Analytics Finance / Commercial team, typically involving large, complex data sets. These teams typically include SQL/ETL engineers, data visualization engineers, product managers, and end users, working in concert with partners in Baker Hughes business units. Potential application areas include visualization tools like Tableau, ThoughtSpot or PowerBI, delta lake technologies such as Databricks and ERP systems like SAP and Oracle.

Responsibilities, authorities and accountability

As a Data Engineer, you will be part of the Data & Analytics Finance / Commercial team, typically involving large, complex data sets. These teams typically include SQL/ETL engineers, data visualization engineers, product managers, and end users, working in concert with partners in Baker Hughes business units. Potential application areas include visualization tools like Tableau, ThoughtSpot or PowerBI, delta lake technologies such as Databricks and ERP systems like SAP and Oracle.

In this role, you will:

• Performing a variety of data loads & data transformations - develop own SQL code satisfying the data requirements given by stakeholders
• Working knowledge of methods for parsing, formatting, & transforming data into units consistent with analytical needs.
• Demonstrating proficiency in implementation of logical/physical data models that support D&A best practices.
• Performing integration of multiple data source-formats into master data load.
• Being proficient in the use of at least one ETL tool.
• Helping envision product roadmap
• Must have good communication skills - both oral and written

Required Qualifications

• Bachelor's Degree. A minimum 2-3 years of professional experience.

Desired Characteristics

Technical Expertise:

• Have exposure and ability to script (SQL, Python, ...) experience
• Have an experience on new D&A (Data & Analytics) application development and existing application optimization is required (data source identification, mapping, ingestion, modelling and transformation for analytical consumption purposes)
• Be able to translates analytics problems into data requirements.
• Be able to understand logical and physical data models, big data storage architecture, data modeling methodologies, metadata management, master data management, data lineage & data profiling.
• Be able to understand the technology landscape, up to date on current technology trends and new technology, brings new ideas to the team.
• Have a hands-on experience with SQL Database such as Oracle MySQL, PostgreSQL, Databricks

Leadership:

• Demonstrated awareness of how to function in a team setting
• Distills information down to key points.
• Expresses the information clearly and concisely. Projects knowledge of relevant data.

Personal Attributes:

• Demonstrated awareness of how to leverage curiosity and creativity to drive business impact
• Asks follow-up questions when presented with new data/projects. Sees the broader implications of an idea.
• Presents new ideas and concepts. Makes connections among previously unrelated ideas.
• Deep passion for learning.