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Cloud Data Engineer

Work set-up: 
Full Remote
Contract: 
Full time
Experience: 
Senior (5-10 years)
Work from: 
Canada

Offer summary

Qualifications:

Minimum of 5 years experience in data engineering and data modeling., Proficiency in Python, Scala, and T-SQL., Strong knowledge of Azure Data Services such as Azure SQL Database, Data Lake, and Databricks., Experience with data pipeline development, orchestration, and automation using tools like ADF and Azure DevOps..

Key responsibilities:

  • Develop and maintain data pipelines and workflows.
  • Design and implement enterprise-scale data architectures.
  • Automate data provisioning and platform integration.
  • Support data security, governance, and compliance initiatives.

LanceSoft, Inc. logo
LanceSoft, Inc. XLarge https://www.lancesoft.com
5001 - 10000 Employees
See all jobs

Job description


Title: DataOps/Cloud Data Engineer
Location: Remote
Duration: 6 Months

Required Skills:
  • +5 years of experience in data engineering, Strong proficiency in Python and familiarity with Azure Services is required.
  • Expertise with Azure Data Services: Azure SQL Database, Azure Data Lake, Azure Storage, Azure Databricks.
  • Experience with data pipeline development, orchestration, deployment, and automation using ADF, Databricks, Azure DevOps/GitHub Actions.
  • Proficiency in Python, Scala, and T-SQL.
  • Solid understanding of data warehousing and ETL concepts including star/snowflake schemas, fact/dimension modeling, and OLAP.
  • Familiarity with DataOps principles, Agile methodologies, and continuous delivery.
  • Proficient in data provisioning automation, data flow control, and platform integration.
  • Knowledge of both structured, semi-structured, and unstructured data ingestion, exchange, and transformation.
  • Experience with cloud-native data services such as DaaS (Data-as-a-Service), DBaaS (Database-as-a-Service), and DWaaS (Data Warehouse-as-a-Service), and infrastructure elements like Key Vault, VMs, and disks.
  • Experience with commercial and open-source data platforms, storage technologies (cloud and on-prem), and the movement of data across environments.
  • Experience in performance monitoring and tuning for cloud-based data solutions.
  • Experience supporting digital product development, data analysis, data security, and secure data exchange across platforms.
  • Proven experience designing enterprise-scale data architectures with high availability and security.
  • Understanding of data governance, data security, compliance, and metadata management.
  • Proficient in entity-relationship (ER) modeling and dimensional modeling.
  • Strong knowledge of normalization/denormalization techniques to support analytics-ready datasets.
Must Haves:
  • 5+ years of experience in data modelling and data engineering is required
  • 5+ Expertise with Azure Data Services: Azure SQL Database, Azure Synapse Analytics, Azure Data Lake, Azure Storage, Azure Databricks
  • 5+ Experience with data pipeline development, orchestration, deployment, and automation using ADF, Databricks, Azure DevOps/GitHub Actions

Required profile

Experience

Level of experience: Senior (5-10 years)
Spoken language(s):
English
Check out the description to know which languages are mandatory.

Hard Skills

Data EngineeringAzure Data Explorer (Kusto)Python (Programming Language)Data ArchitectureData-Flow AnalysisVirtualizationDenormalizationData NormalizationDBaseData Warehouse ArchitecturesDatastaxETL (Extract Transform Load)Data SecurityDimensional ModelingSQL AzureSQL (Programming Language)Data GovernancePerformance AnalyticsAzure Blob StorageData ModelingAzure Data LakeProvisioning ToolsData CollectionAgile Software DevelopmentData TransformationKeychainIntegration PlatformsAzure DatabricksContinuous DeliveryCompliance ManagementScala (Programming Language)Metadata Management
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