Key skills
SQLAIMLGenerative AIETLELTData EngineeringData WarehousingData LakeAnalyticsSnowflakeDatabricksUnit TestingAzureTerraformGitHub ActionsAzure DevOpsAzure SQLOracleSQL ServerGitHubAgileCI/CDChange ManagementCommunication
About this role
goML is a company that builds modern Generative AI, AI/ML, and Data Engineering solutions for enterprises. They are seeking a Data Engineer to design and deliver scalable data pipelines and platforms, translating business needs into technical systems and ensuring high-quality outcomes.
Responsibilities:
- Understand goML’s data engineering frameworks, delivery standards, and Azure architecture patterns
- Deep dive into ongoing client projects, data models, and ETL/ELT workflows
- Collaborate with stakeholders to understand business requirements and data challenges
- Review existing data pipelines and identify opportunities for improvement
- Lead the design and development of data solutions across client engagements
- Build and optimize Azure-based data pipelines using services such as Azure Data Factory, Azure Synapse Analytics, Azure Databricks, and Azure Data Lake Storage (ADLS)
- Implement data transformation and orchestration workflows
- Apply best engineering practices including agile delivery, unit testing, and peer reviews
- Translate business requirements into clear technical designs and implementation plans
- Work closely with cross-functional teams to ensure smooth execution from development to deployment
- Create and maintain technical documentation, solution designs, and test plans
- Own end-to-end delivery of Azure-based data platforms for multiple clients
- Design scalable and flexible cloud-native data architectures aligned with evolving business needs
- Implement and optimize data lakehouse architectures using Azure Synapse or Databricks
- Drive deployment, user onboarding, and change management during project rollouts
- Ensure reliability, performance, security, and data quality across production systems
- Mentor junior engineers and influence data engineering best practices at goML
Requirements:
- 3–7 years of experience in data engineering, preferably in consulting or large-scale solution delivery
- Strong understanding of ETL/ELT processes, data warehousing, and data integration
- Proficiency in SQL / T-SQL and database development
- Hands-on experience with Azure data services (e.g., Azure Data Factory, Azure Synapse, Azure Databricks, ADLS, Azure SQL)
- Experience designing scalable, flexible data solutions driven by business requirements
- Experience with backend databases (e.g., SQL Server, Oracle) and/or ETL tools
- Familiarity with data modeling techniques (star/snowflake schemas)
- Bachelor's or Master's degree in Computer Science, Information Systems, or a related field
- Experience working with multiple client stakeholders and delivery teams
- Exposure to modern cloud-native data stacks and lakehouse architectures
- Familiarity with CI/CD practices for data pipelines (Azure DevOps, GitHub Actions)
- Experience with infrastructure-as-code (e.g., Terraform, ARM templates)
- Strong documentation and communication skills