G2/19 NB D - Data Engineer

Real opportunities. Real impact. Your career, redefined.

(NOTE: A human reviews every application at Oceans, so please apply for only one position and only once a year—if you're a better fit for another role, we’ll route your application accordingly and if we’re not quite ready for you, we’ll reach back out later).

At Oceans, we believe that talent knows no boundaries. That’s why we connect the best and brightest professionals with career-defining opportunities that challenge, inspire, and accelerate their career growth. Our community doesn't just work—they dive deep, solve complex challenges, and make a real impact with global industry leaders. And in doing so, they don’t just support bold ideas—they expand their skills, broaden their expertise, and grow their careers.

As a Data Engineer, you will architect and implement the full data foundation powering an internal LLM-driven analytics platform integrated directly with Amazon Seller Central. You will own ingestion, normalization, warehousing, semantic modeling, and query-ready access across commerce, advertising, operational, and financial datasets spanning multiple client brands.

This role blends deep data engineering, Amazon SP-API specialization, analytics architecture, and LLM enablement, requiring strong ownership and systems thinking to deliver a reliable, scalable BI platform that supports natural-language analytics for Amazon sellers.

Accountability

Your success as a Data Engineer will be defined by the scalability, reliability, and auditability of the Amazon data platform you build, enabling deterministic analytics, trusted business insight, and future product expansion.

Here’s how you’ll make an impact:

Amazon Data Ingestion & Integration

• Establish and manage authenticated SP-API connections across client brands.
• Ingest data from Orders, Reports, Advertising, Inventory, and Financial endpoints.
• Handle throttling, pagination, retries, and rate-limit constraints reliably.
• Implement incremental loads, historical backfills, and failure recovery.
• Continuously expand usable Amazon dataset coverage.

Data Pipeline & Warehouse Architecture

• Design and implement scalable ELT/ETL pipelines from raw ingestion to analytics-ready schemas.
• Stand up and operate a centralized warehouse (e.g., Snowflake, BigQuery, Redshift, Postgres, or equivalent).
• Normalize multi-client, multi-brand datasets with historical retention and versioning.
• Model core domains including sales, advertising performance, inventory/FBA, and profitability.
• Ensure long-term maintainability, observability, and scale readiness.
  

Semantic Layer & LLM Query Enablement

• Define standardized ecommerce metrics (sales, net revenue, ad spend, TACoS, and related drivers).
• Create curated semantic or mart layers suitable for deterministic LLM querying.
• Implement guardrails for filters, date logic, and metric definitions.
• Ensure query outputs are reproducible, traceable, and grounded in source-of-truth tables.
• Partner with founders on LLM model and architecture decisions.

Data Quality, Monitoring & Reliability

• Implement validation, anomaly detection, and freshness SLAs.
• Maintain logging, alerting, and incident-response readiness across pipelines.
• Ensure auditability and accuracy of analytics outputs.
• Proactively resolve reliability risks and operational gaps.

Documentation & Operational Continuity

• Document API integrations, schemas, refresh cadences, and assumptions.
• Produce clear handoff materials enabling internal continuity.
• Prepare architecture for secure multi-tenant, external-facing product evolution.
• Maintain a documentation-first, long-term ownership mindset.

Colleagues

You will work directly with the client’s founders as the primary technical owner of the data platform, collaborating on architecture, LLM strategy, and product readiness.

Within Oceans, you’ll receive guidance from your Operations Manager to support delivery excellence, professional growth, and long-term success in the role.

Skills & Qualifications

At Oceans, we believe in T-shaped individuals—those who bring deep expertise in one area paired with broad curiosity across the business. As a Data Engineer (Pirate), your vertical focus will be building reliable, scalable data architecture, while your horizontal focus will include ecommerce analytics understanding, LLM readiness, and pragmatic product thinking.

To excel in this role, you should have:

• 4–6 years of experience in data engineering, analytics engineering, or backend data infrastructure within a fast-paced or high-growth environment.
• Strong proficiency in building and maintaining scalable data pipelines, including ETL/ELT workflows, data modeling, and performance optimization across modern data stacks.
• Hands-on experience with cloud data platforms and orchestration tools, with the ability to ensure reliability, observability, and efficient data flow across systems.
• Ability to collaborate closely with analytics, product, and business stakeholders, translating data requirements into structured, reliable, and well-documented data solutions.
  

Diversity of experience is core to Oceans. You are expected to work inclusively with individuals from a variety of backgrounds, ensuring that both personal and collective dignity are supported.

During the interview process, you’ll have the opportunity to showcase your skills in the following areas:

• Data Architecture & Systems Thinking: How you design scalable, reliable data platforms that support real business decisions.
• Amazon Data Integration Mastery: How you handle SP-API constraints, ingestion complexity, and ecommerce dataset modeling.
• Analytics Modeling & Metric Design: How you translate business logic into trustworthy semantic data layers.
• LLM-Ready Data Enablement: How you ensure deterministic, auditable AI-driven analytics querying.
• Reliability, Monitoring & Ownership: How you operationalize pipelines for long-term accuracy and resilience.
• Documentation & Continuity Mindset: How you build systems that remain understandable, maintainable, and extensible.

Role Specifications

This is a remote role, where you will be expected to work a split shift with some overlap with our client’s time zone. You will, however, be expected to be present for in-person training programs during your first 90 days with us. During the offer process, we’ll share more information about our benefits and compensation philosophy, considering both market trends and individual factors.

About Oceans

At Oceans, we build remote teams that connect the world’s top 1% of talent with visionary leaders. With us, you’re not just doing a job—you’re redefining your career with opportunities designed to unlock your potential. We welcome the chance to discuss the complementary parts of our business during your interview process and encourage questions about where we are and where we are going.