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We are seeking an experienced Senior Data Engineer with expert-level skills in PySpark and hands‐on experience building ETL pipelines, data lake architectures, and data feed integrations on AWS to join our team.You will work with both structured and unstructured data, ingesting from multiple on‐premises and enterprise data sources such as SAP, Intelex, SQL, and OSI PI into AWS.This role offers the opportunity to contribute to large‐scale data solutions and collaborate with cross‐functional teams in a dynamic environment.ResponsibilitiesDesign, develop, and optimize ETL pipelines using PySpark and AWS Glue Jobs to process large volumes of structured and unstructured dataOrchestrate data workflows with Apache Airflow, ensuring reliable scheduling, dependency management, and robust error handlingBuild and maintain data feeds from on‐premises and enterprise systems into AWS data lake environmentsIntegrate with enterprise data sources including SAP for ERP and operational data, Intelex for environmental, health, safety, and quality data, SQL databases for relational data, and OSI PI for real‐time industrial and process historian dataDevelop and manage API interactions to extract data from on‐premises services into AWSHandle data extraction, transformation, and loading across various formats and protocolsSupport the design and maintenance of AWS data lake architectures using Amazon S3, AWS Glue, and Lake FormationEnsure data is cataloged, partitioned, and optimized for analytics and reportingImplement data quality checks, validation,



and lineage tracking across all pipelinesRequirementsMinimum 3 years of experience in data engineering rolesAdvanced proficiency in Python and PySpark for data processing and pipeline developmentStrong background in Extract, Transform, Load (ETL) processesExperience orchestrating workflows with Apache AirflowProven track record building production‐grade data pipelines on AWSHands‐on experience with AWS Glue Jobs for ETL processingFamiliarity with Amazon S3, data lake patterns, and data cataloging techniquesExperience using AWS‐native monitoring and operational toolsSkilled in integrating with enterprise systems via APIs, JDBC, or native connectors, including SAP, Intelex, SQL databases, and OSI PIAbility to work with both structured and unstructured data formatsExcellent documentation, communication, and collaboration skillsEnglish communication skills at B2+ level or higher, both written and spokenNice to haveFamiliarity with energy, oil & gas, or industrial data environmentsUnderstanding of Drilling and Completions data flows and terminologyWe offerInternational projects with top brandsWork with general teams of highly skilled, diverse peersEmployee financial programsPaid time off and sick leaveUpskilling, reskilling and certification coursesUnlimited access to the LinkedIn Learning library and 22,000+ coursesGlobal career opportunitiesVolunteer and community involvement opportunitiesEPAM Employee GroupsAward‐winning culture recognized by Glassdoor, Newsweek and LinkedIn#J-*****-Ljbffr

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📌 Senior Data Engineer (Python & Aws) (Luján de Cuyo)
🏢 EPAM Systems
📍 Luján de Cuyo