Job Openings Data Engineer with GCP

About the job Data Engineer with GCP

Title of Position: Data Engineer

Our main goal is to Generate Business Impact through Data & Analytics and fulfill the strategic goals, by:

  • Execute the IBU and Global Data & Analytics Strategy.
  • Enabling a data-driven mindset that continuously scales data-fueled ways of working.
  • Achieve/Enable Data Self Service.
  • Partner with business to identify process issues and support data governance in a non-invasive approach.


Summary of the position:

Data engineers work in a variety of settings to build systems that collect, manage, and convert raw data into usable information for data scientists and business analysts to interpret. Their goal is to make data accessible so that organizations can use it to evaluate and optimize their performance.

As part of its functions and responsibilities, and in coordination with the Data Management Lead, Data Science Team, Project Managers and Business Relationship Leaders, it must also carry out the analysis, studies and lead the work for the materialization of the projects related to its responsibilities and functions.

Duties and Responsibilities:

  1. 1. Supports data platform building, operation, and maintenance.
  2. 2. Acquire datasets that align with business needs.
  3. 3. Ensure data is processed in a stable and reliable way
  4. 4. Develop algorithms to transform data into useful, actionable information.
  5. 5. Build, test, and maintain database pipeline architectures.
  6. 6. Create new data validation methods and data analysis tools.
  7. 7. Ensure compliance with data governance and security policies.
  8. Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.


Communications and Challenges:

The main internal contacts are: Regional/Global digital relationship leaders, as well as all business units.

The main external contacts are: Service and outsourcing providers, IT manufacturers and startups; as well as innovation and digital transformation organizations.

Job challenges are: deep understanding in artificial intelligence and machine learning, but also need the skills to effectively communicate with multiple business units.

The position participates in: integrating the organization towards a collaboration and innovation culture reflecting a business strategy leveraging the use of Data.

Qualifications and Experience:

  • Bachelor´s degree in IT/Digital Areas

Experience:

  • 2 years minimum experience Data Analysis / Engineering.
  • Coding: Proficiency in coding languages is essential to this role. Common programming languages include SQL, NoSQL, Python, Java, R, and Scala.
  • Relational and non-relational databases: Databases rank among the most common solutions for data storage. You should be familiar with both relational and non-relational databases, and how they work.
  • ETL (extract, transform, and load) systems: ETL tools include Xplenty, Stitch, and Talend (preferred).
  • Data storage: Not all types of data should be stored the same way, especially when it comes to big data. As you design data solutions, know when to use a data lake versus a data warehouse.
  • Automation and scripting. Automation is a necessary part of working with big data simply because organizations can collect so much information. Experience writing scripts to automate repetitive tasks.
  • Experience building and optimizing big data pipelines, architectures, and data sets.
  • Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement.
  • Experience with enterprise data governance frameworks, data cataloging tools and processes using the best practices in the market (Preferred).
  • Google (GCP) BigQuery experience.
  • Good Analytical and communication skills.
  • Good scripting and programming skills (Preferred).
  • Dot connector / Problem-solving skills.
  • Good communication in English (oral and written).
  • Knowledge in:
  • General Information Technology
  • Big Data Analytics
  • Artificial Intelligence and Machine Learning
  • Data Visualizations
  • SQL and Non-SQL

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