IT Data Engineer

Key Relationships:

• Internal – Regional Retail Business Manager, in-country Retail Business Managers, Convenience Retail Leads, Loyalty Managers, Regional IT Management, Global Data Analytic Team, LATAM Data Analytic Team.
• External – Data visualization developers, Retail Information Systems owners and manufacturers, External data solution providers.

Function:

IT Data Engineer will play a critical role in designing, building, and maintaining the organization's data infrastructure to support business decision-making and analytical efforts. This individual will be responsible for developing robust data pipelines, optimizing data workflows, and ensuring data accessibility and quality across various business units.

By leveraging Databricks, Data Factory, SQL, and Python, the role aims to transform raw data into usable formats, enabling efficient data analysis and reporting.

Additionally, the position requires close collaboration with stakeholders, including analysts, data scientists and business teams in order to align technical solutions with business needs. The IT Data Engineer will also contribute to establishing best practices for data governance, security, and documentation, while continuously improving data processes and staying up-to-date with advancements in data engineering technologies.
 

Also, role contribution can help analysts and managers improve business, extracting useful data from various and different databases, developing and maintaining data models, and performing or leading data modeling.

Key Responsibilities:

1- Understand databases and analytical thinking

• Collaborate with cross-functional teams to ensure data quality, accuracy, and consistency across our databases and data silos
• Intermediate-Advanced knowledge on datawarehousing and datalake concepts
• Intermediate-Advanced knowledge on relational DBs, data models/concepts (dimensional, fact, normalized database, star schema, views, stored procedures, etc.)
• Analytical thinking and autonomy skills for ad-hoc data analysis and strategies related to data solutions

2- Extract and transform data

• Stay current with emerging technologies and methodologies related to data analytics and data engineering.
• Advanced knowledge on SQL
• Intermediate-Advanced knowledge on Python and PySpark
• Extract and transform data using ETL’s tools like Azure Data Factory and Databricks
• Research automation processes and leverage automation to allow focus on high-impact activities
• Propose data base improvements or solution such as data base links, views and queries
• Identify data that could be valuable to the business and plan its extraction

3- Develop Data models

• Design, build and maintain data models in tools like Databricks, Azure Synapse DWH or Sigma Computing to provide fast and reliable data solutions to business and IT
• Design and implement data models that accurately reflect business processes and support analytical requirements.

4- Transform business data requirements into data solutions

• Work with stakeholders to understand their data and analytics needs and develop appropriate solutions.
• Understand the business requirements and be able to convey the needs to the IT Team
• Provide training and support to business users as needed.
• Calculate workload demand to manage business expectations.
• Be able to manage demand from business and creates synergy with global Data Analytic team in order to manage the DA Architecture for regional purposes.

5- Data quality and documentation

• Design, suggest and maintain strategies for data quality validation and data curation
• Document existing and new data pipelines, workflows, alerts or any process related to data analytics
• Collaborate with cross-functional teams to ensure data quality, accuracy, and consistency.

Requirements:

• Speak Spanish and English fluently
• Capable of managing multiple initiatives
• Available for possible relocation or traveling

Experience:  

• 3+ years of experience in data engineering/analytics/data science/insights/strategy
• Bachelor’s degree ideally in a technology or quantitative subject (e.g. computer science, mathematics, engineering, science)
• 3+ years of experience with data engineering tools and practices (Databricks, Azure Data Factory, Datawarehousing, SQL, Python, PySpark, ETL’s / ELT’s, Data Studio, or similar technologies)
• 3+ years of experience with data visualization and analysis tools (Power BI,Tableau, Power Pivot, Power Query) desirable
• Experience integrating different IT systems
• Multicultural environment experience
• Proven ability to translate business requirements into data solutions
• Knowledge of Energy industry and Convenience Retail businesses and key processes desirable

Skills: 

• Good stakeholder management experience and comfortable presenting to senior leadership
• Communication, analytical and organizational skills
• Autonomy and self-learning skills
• Interpersonal skills and team working also virtually
• Ability to multi-task, prioritize and coordinate resources

Competencies:

• Strongly organized and structured
• Important to be able to work with the business users at all level of the organization
• Able to prioritize work
• Creative, innovative and autonomous
• Strong team player
• Stakeholder management skills