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 (AWS) 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 close to 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 AWS architecture patterns
Deep dive into ongoing client projects, data models, and ETL 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 ETL pipelines and data integration 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 AWS-based data platforms for multiple clients
Design scalable and flexible data architectures aligned with evolving business needs
Drive deployment, user onboarding, and change management during project rollouts
Ensure reliability, performance, 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 processes, data warehousing, and data integration
Proficiency in SQL / PL SQL and database development
Experience designing scalable, flexible data solutions driven by business requirements
Hands-on experience with AWS data services
Experience with backend databases (e.g., Oracle) and/or ETL tools (e.g., Informatica)
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 data lake architectures
Familiarity with CI/CD practices for data pipelines
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

Engineer the Data Backbone for AI with goML

Why You? Why Now?

What You’ll Do (Key Responsibilities)

First 30 Days: Context & Discovery

Understand goML’s data engineering frameworks, delivery standards, and AWS architecture patterns
Deep dive into ongoing client projects, data models, and ETL 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 ETL pipelines and data integration 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 AWS-based data platforms for multiple clients
Design scalable and flexible data architectures aligned with evolving business needs
Drive deployment, user onboarding, and change management during project rollouts
Ensure reliability, performance, 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 processes, data warehousing, and data integration
Proficiency in SQL / PL SQL and database development
Experience designing scalable, flexible data solutions driven by business requirements
Hands-on experience with AWS data services
Experience with backend databases (e.g., Oracle) and/or ETL tools (e.g., Informatica)
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 data lake architectures
Familiarity with CI/CD practices for data pipelines
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

Data Engineer

What we know about this role

Skills required

Job description

Engineer the Data Backbone for AI with goML

Why You? Why Now?

What You’ll Do (Key Responsibilities)

First 30 Days: Context & Discovery

First 60 Days: Build & Deliver

First 180 Days: Ownership & Scale

What You Bring (Qualifications & Skills)

Must-Have

Nice-to-Have

Who You Are

Why Work With Us?

Tools to land this role

Ground Reality

Spot the dealbreakers in this 514-word post before you apply

Insider Path

Find someone who can refer you here

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Data Engineer

What we know about this role

Skills required

Job description

Engineer the Data Backbone for AI with goML

Why You? Why Now?

What You’ll Do (Key Responsibilities)

First 30 Days: Context & Discovery

First 60 Days: Build & Deliver

First 180 Days: Ownership & Scale

What You Bring (Qualifications & Skills)

Must-Have

Nice-to-Have

Who You Are

Why Work With Us?

Tools to land this role

Ground Reality

Spot the dealbreakers in this 514-word post before you apply

Insider Path

Find someone who can refer you here

Get tomorrow's jobs before you have to search

Someone shared one job with you. ASAI keeps finding the rest.