We are looking for a motivated and technically solid L1 Data Engineer to join our growing Data & Analytics team. In this role, you will be responsible for designing, building, and maintaining the data architecture and infrastructure that supports our organization's data strategy. You will work hands-on to develop, test, and deploy reliable data solutions — ensuring pipelines are scalable, efficient, and aligned with business requirements.This is an ideal opportunity for a data professional who is eager to deepen their expertise in cloud-native data platforms, particularly within the Microsoft Azure and Databricks ecosystem, and who thrives in a collaborative, fast-paced environment.Key Responsibilities Design, develop, and maintain scalable data pipelines and ETL/ELT workflows to support business intelligence and analytics use cases Build and optimize data ingestion processes using Azure Data Factory and Databricks, ensuring data quality and consistency across all layers of the data platform Transform and process large datasets using PySpark and Python, applying best practices for performance and maintainability Write and optimize complex SQL queries to support analytical reporting and data validation requirements Collaborate with data architects and senior engineers to implement and maintain data models aligned with organizational standards Monitor, troubleshoot, and resolve pipeline failures and data quality issues, applying root-cause analysis to prevent recurrence Contribute to documentation of data pipelines, data dictionaries, and engineering standards Support the team in exploring and evaluating new tools and approaches to continuously improve the data infrastructureRequirements2+ years of professional experience in a Data Engineering or closely related roleStrong proficiency in Python for data processing, transformation, and automation tasksHands-on experience with Pandas for data manipulation and PySpark for distributed data processingPractical experience with Databricks, including notebook development, clusters, and job orchestrationExperience building and managing data pipelines with Azure Data FactoryWorking knowledge of Azure Synapse Analytics, particularly Spark pool integrationSolid SQL skills, including query writing, optimization, and performance tuningFamiliarity with data engineering principles including incremental loading, data lake architecture, and Delta LakeUnderstanding of data governance and security concepts within a cloud data platformNICE TO HAVEExperience with SQL Server migration projects, including schema conversion and data movementExposure to Terraform for Azure infrastructure provisioning and managementFamiliarity with CI/CD practices applied to data engineering workflowsExperience with Delta Sharing or Lakehouse Federation conceptsCERTIFICATION REQUIREMENTCandidates are expected to hold or be actively working toward the Databricks Certified Data Engineer Associate certification. This certification validates foundational knowledge across the following domains:Databricks Lakehouse Platform architecture and capabilitiesETL and ELT workflows using Spark SQL and PySparkIncremental data processing and structured streamingProduction pipeline development and orchestrationData governance and security within the Databricks environment