JOB DETAILS
Data Engineer
CompanyDatavail
LocationUsa
Work ModeRemote
PostedSeptember 5, 2026
About The Company
Datavail | Data, Cloud & AI—Built for Real Business Outcomes
Datavail is a data, cloud, and AI consultancy that helps organizations turn complex technology environments into clear, measurable business outcomes.
We partner with data, technology, and IT leaders to make enterprise data more usable, systems more adaptable, and decisions more informed. Our work sits at the intersection of data management, cloud modernization, enterprise applications, and AI—bringing these disciplines together so they support the business, not slow it down.
In a landscape full of tools, platforms, and transformation promises, Datavail focuses on what actually drives progress:
• Trusted, well-managed data that teams can rely on
• Cloud environments without unnecessary cost or complexity
• Enterprise applications that evolve with the business
• Practical, responsible AI that delivers value—not experiments
We help organizations:
• Improve data quality, accessibility, and governance
• Turn analytics and AI into everyday decision-making tools
• Modernize and optimize cloud and application environments
• Reduce operational risk while increasing agility and performance
Our Core Capabilities:
• Data Management & AI: Data foundations, analytics, AI and machine learning that support real-world decisions
• Cloud Services: Cloud modernization, optimization, SRE services, and license optimization
• Enterprise Applications: Managed services, upgrades & integrations, digital transformation, and implementation services
At Datavail, we believe data only creates value when it’s well managed, well understood, and actively used. Our role is to help organizations move from complexity to clarity—and from data to action.
About the Role
- Azure Data Engineer with 6+ years of experience designing, developing, and optimizing enterprise-scale data platforms using Microsoft Azure and Snowflake
- Proven expertise in building scalable data pipelines, data warehouses, and analytics solutions leveraging Azure Data Factory (ADF), Azure Databricks, Azure Synapse Analytics, Snowflake, Python, SQL, and Spark
- Experienced in data modeling, ETL/ELT development, cloud migration, performance tuning, data governance, and implementing CI/CD practices
- Strong background in integrating data from multiple sources and enabling business intelligence and advanced analytics solutions
Key Skills: - Azure Data Factory (ADF)
- Azure Databricks
- Azure Synapse Analytics
- Snowflake Data Cloud
- Python, PySpark, SQL
- Azure Data Lake Storage (ADLS Gen2)
- Azure Functions
- Delta Lake
- Data Warehousing & Data Modeling
- ETL / ELT Development
- CI/CD (Azure DevOps, Git)
- Performance Tuning & Optimization
- Data Governance & Security
- Power BI Integration
- Agile & Scrum Methodologies
What you will do:
- Design, develop, and maintain scalable data engineering solutions on Azure and Snowflake platforms
- Build and optimize ETL/ELT pipelines using Azure Data Factory, Databricks, and Snowflake to ingest, transform, and load data from various structured and unstructured sources
- Develop and maintain enterprise data warehouses, data marts, and analytical datasets supporting reporting, BI, and advanced analytics initiatives
Implement data transformation and orchestration processes using PySpark, SQL, Python, and Snowflake stored procedures - Design and manage cloud-based data lakes using Azure Data Lake Storage (ADLS Gen2) and Delta Lake architecture
- Collaborate with business stakeholders, data analysts, and architects to gather requirements and translate them into scalable data solutions
- Monitor and optimize data pipeline performance, ensuring reliability, scalability, and cost efficiency
- Implement data quality frameworks, validation rules, and monitoring processes to ensure accurate and trusted data
- Manage Snowflake objects including databases, schemas, warehouses, tasks, streams, and data-sharing capabilities
- Develop and maintain dimensional and normalized data models following industry best practices
- Implement security controls, access management, encryption, and governance policies across Azure and Snowflake environments
- Support cloud migration and modernization initiatives from on-premises or legacy platforms to Azure and Snowflake
- Automate deployment processes using Azure DevOps, Git repositories, and CI/CD pipelines
- Troubleshoot production issues, perform root cause analysis, and provide timely resolution for data-related challenges
- Participate in Agile ceremonies, code reviews, and technical design discussions to ensure high-quality solution delivery
- Create technical documentation, architecture diagrams, operational runbooks, and knowledge-transfer materials
Preferred Certifications: - Microsoft Certified: Azure Data Engineer Associate (DP-203)
- SnowPro Core Certification
Datavail is a leading provider of data management, application development, analytics, and cloud services, with more than 1,000 professionals helping clients build and manage applications and data via a world-class tech-enabled delivery platform and software solutions across all leading technologies. For more than 17 years, Datavail has worked with thousands of companies spanning different industries and sizes, and is an AWS Advanced Tier Consulting Partner, a Microsoft Solutions Partner for Data & AI and Digital & App Innovation (Azure), an Oracle Partner, and a MySQL Partner.
Key Skills
Azure Data FactoryAzure DatabricksAzure Synapse AnalyticsSnowflake Data CloudPythonPySparkSQLAzure Data Lake StorageAzure FunctionsDelta LakeData WarehousingData ModelingETL/ELT DevelopmentCI/CDAzure DevOpsGit
Categories
Data & AnalyticsTechnologySoftwareEngineeringConsulting
Job Information
📋Core Responsibilities
Design, develop, and maintain scalable data engineering solutions using Azure and Snowflake platforms. Build and optimize ETL/ELT pipelines to ingest, transform, and load data from various sources while ensuring data quality and security.
📋Job Type
full time
📊Experience Level
5-10
💼Company Size
917
📊Visa Sponsorship
No
💼Language
English
🏢Working Hours
40 hours
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