Principal Data Engineer

Bunge Iberica SA; São Paulo; Sur place; BRL 180 000 - 300 000; Plein temps

Résumé du poste

Bunge Iberica SA in São Paulo, Brazil, seeks a Principal Data Engineer to lead data architecture and engineering across analytics projects. You will build scalable data pipelines, mentor engineers, and collaborate with business analysts and architects to deliver strategic data solutions.

Ideal candidates have strong SQL, Python or Scala, and hands-on experience with cloud data tools (BigQuery, Dataform, Airflow).

Qualifications

• Proficient in SQL and data analysis.
• Experience with Python or Scala.
• Understanding of data mesh concepts.
• Ability to structure data solutions for business needs.

Responsabilités

• Develop and maintain data pipelines for analytics.
• Lead evaluation and deployment of new analytic data engineering tools.
• Mentor junior data engineers on data standards and practices.
• Collaborate with business analysts and architects on enterprise initiatives.
• Communicate analytics capabilities and educate teams.

Connaissances

SQL

Python

Scala

Data analysis

Data mesh concepts

Formation

PhD in STEM

5+ years experience as Data Engineer II

Outils

BigQuery

DataForm

Cloud Functions

Airflow/Composer

Terraform

Scheduler

Description du poste

Principal Data Engineer

Principal Data Engineer

Role Purpose Statement

We are seeking a highly motivated and experienced Lead Data Engineer with strong expertise in data architecture,data engineering, data analysis, reporting, and a basic understanding of data science techniques and workflows. They are an Agile learner, possess strong problem-solving skills, work as partof a technical, cross functional analytics team, and want to solve complex data problems and deliver the insights to enable analytics strategy. At Bunge, you will be at the forefront ofleveraging data analytics and technology to feed and fuel the world in a better, faster, and simpler way. Data Engineer will work closely with a multidisciplinary Agile team to build high quality data pipelines driving analytic solutions. These solutions will generate insights from the organization'sconnected data, enabling the organization to advance the data-driven decision-making capabilities of the organization's enterprise.

Main Accountabilities

• Solve complex data problems to deliver insights thathelps the organization's business to achieve theirgoals
• Create data products for analytics and data scientistteam members to improve theirproductivity
• Mentor and coach other data andanalytic professionals on data standards andpractices
• Foster a culture of sharing, re-use, design for scalestability, and operational efficiency of data andanalyticalsolutions
• Lead the evaluation, implementation and deployment ofemerging tools and process for analytic dataengineeringin order to improve the organization'sproductivity as ateam
• Develop and deliver communication and educationplans on analytic data engineering capabilities,standards, andprocesses.
• Partner with business analysts and solutions architectsto develop technical architectures for strategicenterprise projects andinitiatives.
• Learn about machine learning, data science, computervision, artificial intelligence, statistics, and/or appliedmathematics
• Ensure timely analysis and testing for regular maintenance of solutions over time
• Learn about machine learning, data science, computervision, artificial intelligence, statistics, and/or appliedmathematics

4. Impact/Dimensions:

Establishes and implements organization, function and/or sub-function short to mid term (1-3 years) strategy. Projects/initiatives lead have impact on business on a domestic or international scale; Is recognized as an external thought leader within strategic function or discipline.

Key Performance Indicators (KPIs)

Accountable for the results of a large and/or moderately complex project(s). Provides input on resource planning and policy development.

Responsible for the roadmap execution and adjustment

5. Major Opportunities and Decisions:

The problems faced are difficult and often complex and multi-dimensional. Decisions and problem-solving are guided by policies, procedures, and business plan; Anticipates and interprets internal or external issues and recommends solutions/best practices. Applies acquired expertise to analyze and solve problems without clear precedent.

6. Management/Leadership:

Manages operational plans, large projects and/or processes with limited oversight from manager. Leads and/or participates with comparable influence in large projects/initiatives; AND/OR provides leadership to professionals and support. Contributes to short to mid term (1-3 years) talent optimization plans to execute on strategies in job area.

7. Key Relations:

Stakeholders of this role include Leadership team members, business leaders as well as technical experts making highly developed interpersonal & soft skills are important. One should be tech-savvy and business-savvy as well, should understand business, different types of data analytics technologies, apply methods to valuable authentication, prevent frauds. It is crucial to shape data products in alignment with corporate strategy and provide data insights leading to business directions

8. Knowledge and Technical Competencies:

• Proficient in SQL and data analysis and experience with at least one programming language (Python or Scala preferred)
• Conceptual understanding of data mesh
• Can help business structure the data solution.
• Develop business awareness of possible use cases.
• Python
• Bigquery
• DataForm
• Cloud Functions
• Airflow/Composer
• Scheduler
• Terraform

Education & Experience

• PhD in STEM field and 2+ years experience or 5+ years experience as Data Engineer II
• Plays a significant role in developing other juniors, act as a technical consultant to product managers, and valued as an asset to any data science projects.
• Domain expert and functional advisor for business stakeholders
• Handle most of the day-to-day communications with the product owners.
• Leads all internal meetings as well as weekly or fortnightly reports on the team’s progress.
• Divide their project into workstreams led by Senior Data Engineers and delegate tasks efficiently. Ensure that the project is well executed and deliverables are completed according to the timeline.