Associate Data Engineer - Builders Program

Overview

About the role

• We’re looking for a fresh graduate or early-career **Data Platform Engineer** on a builder track.
• This role is for someone who wants to build the foundations behind analytics and AI.
• You will help develop and run the data platform that makes data **available, secure, governed, and fast**.
• That includes pipelines, event streaming ingestion, warehouses and lakes, and the guardrails that keep data trusted.
• With the advancement of AI, we care more about strong fundamentals than memorizing tools.
• Use AI assistants to move faster, but always own correctness, reliability, and security.
• Your responsibilities
• **Build and maintain the data platform**
• + Help develop and maintain platform architecture (data warehouse, data lake, governance, protection).
• + Keep the platform reliable, observable, and ready to scale.
• **Build robust pipelines (ELT/ETL + event-driven)**
• + Build the infrastructure required for optimal extraction, transformation, and loading using SQL and big data technologies.
• + Augment batch pipelines with event-driven patterns where it makes sense (streaming ingestion, CDC, near-real-time processing, and reliable delivery).
• + Improve pipeline performance, cost, and reliability.
• **Make the platform easier every week**
• + Identify, design, and implement internal improvements: automate manual processes, optimize data delivery, and redesign components for scalability.
• **Enable analytics and AI use cases**
• + Build platform primitives and data products that power self-serve analytics and AI-assisted insights (not only dashboards).
• + Support analytics tooling that uses the pipelines to deliver actionable insights into customer acquisition, operational efficiency, and key business metrics.
• **Partner with stakeholders**
• + Work with stakeholders including Executive, Product, Data, and Design teams to resolve data technical issues and support infrastructure needs.
• **Keep data secure across boundaries**
• + Help keep data separated and secure across national boundaries, including through multiple data centers and appropriate access controls.
• Your expertise (must have)
• Fresh graduate or **\< 1 year** of relevant experience (internships and projects count).
• Solid programming fundamentals in **Python**, **Java**, **Go**, or similar.
• Strong **SQL fundamentals**.
• Understanding of data concepts: schemas, partitions, data quality, SLAs, and basic security/PII awareness.
• A problem-solving mindset and comfort debugging systems end-to-end.
• Clear communication and a collaborative approach.
• Nice to have
• Familiarity with cloud data stack concepts (warehouses, object storage, orchestration, streaming).
• Exposure to event streaming (Kafka concepts like topics, partitions, consumer groups) or CDC.
• Experience with dbt, Airflow, Spark, or similar tools (coursework or projects count).
• Basic Terraform/IaC and CI/CD familiarity.
• Experience using AI assistants responsibly for coding, debugging, and documentation.
• What success looks like
• You ship at least one production-ready pipeline or platform improvement that reduces toil or improves reliability.
• You can debug a data issue from source to downstream consumption with clear root cause and fix.
• Teams can onboard to data sources faster, with better documentation and fewer manual steps.
• Platform reliability and data quality improve in measurable ways (latency, failures, freshness, or coverage).