Data Engineer

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

Who You Are Comfortable leading data solution design and execution Methodical, detail-oriented, and quality-focused Able to translate complex business needs into clear technical outcomes A strong collaborator who works well across teams and clients

Why Work With Us? Remote-first role with flexible collaboration Work on diverse client projects across industries High ownership and visibility in data platform delivery Opportunities to grow into

Solution Architect or Technical Lead

roles A culture driven by learning, ownership, and impact