Data Engineer

Be an Early ApplicantFull Timejunior

Ahmedabad, Gujarat, INPosted March 20, 2026

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SQLAzureTerraformGitHub ActionsSnowflakeGitHubAgileCI/CDDevOps

Job Description

Engineer the Data Backbone for AI with goML

At goML, we build modern Generative AI, AI/ML, and Data Engineering solutions that help enterprises turn data into intelligent, scalable systems. Our mission is to bridge advanced data platforms with real-world business needs—enabling faster insights, smarter decisions, and AI-ready foundations.

We’re looking for a Data Engineer (Azure) to join our growing team. In this role, you’ll design and deliver robust, scalable data pipelines and platforms across multiple client engagements. If you enjoy solving complex data problems, working closely with customers, and building production-grade data systems, you’ll thrive here.

Why You? Why Now?

As enterprises modernize their data stacks to support analytics, AI, and GenAI use cases, strong data engineering becomes mission-critical. This role is ideal for someone who enjoys owning data solutions end to end, translating business needs into technical systems, and delivering high-quality outcomes in fast-moving environments.

What You’ll Do (Key Responsibilities)

First 30 Days: Context & Discovery

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

First 60 Days: Build & Deliver

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

First 180 Days: Ownership & Scale

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

What You Bring (Qualifications & Skills)

Must-Have

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

Nice-to-Have

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