Data Engineer
Position Overview (Remote all Latam)
As a Data Engineer, you will play a pivotal role in ensuring effective storage, integration, and utilization of data across the Retail portfolio. You'll collaborate with cross-functional teams to align data strategies with organizational goals, optimize data systems, and ensure data security and compliance.
Key Accountabilities
Collaborate with cross-functional teams to align data engineering practices with business objectives.
Create conceptual, logical, and physical data models to support business requirements.
Determine organizational data needs and translate them into robust data architectures.
Define and enforce data architecture standards, policies, and procedures for effective data management, governance, and archival strategies.
Develop and implement data migration strategies from legacy systems.
Develop ETL/ELT pipelines in Azure Data Factory and Databricks.
Integrate usage history, weather data, pricing curves, and product terms into standardized models.
Build and optimize Delta Lake tables in ADLS for staging, reference, and historical use cases.
Enable workflows through Azure Notebooks and Databricks jobs.
Essential Skills and Experience
Experience with Azure Data Factory, Databricks, and Azure-based data solutions.
Strong knowledge of ETL/ELT processes, data modeling, SQL, and data warehousing.
Familiarity with Delta Lake and Azure Data Lake Storage.
Ability to work collaboratively with cross-functional teams.
Proven experience in data modeling.
Familiarity with cloud data platforms (e.g., Azure, AWS, Google Cloud) and big data technologies.
Experience with data governance, data quality, and data security best practices.
Ability to work collaboratively with cross-functional teams and communicate complex technical concepts to non-technical stakeholders.
Strong problem-solving, analytical, and organizational skills.
Desired Qualifications
Certifications in data architecture, cloud platforms, or data management (e.g., AWS Certified Data Analytics, Google Professional Data Engineer, DAMA).
Experience with data visualization tools (e.g., Power BI, Tableau) and programming languages (e.g., Python, Java) is a plus.
Knowledge of industry-standard data models and regulatory requirements.
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