OA - Data Analyst

Ocean Advisor Data Analyst

Description:

Data Technologist

Company:

Ocean Advisor

Target Start Date:

June 1, 2026

Location:

Laguna Niguel, CA (Hybrid)

Compensation:

$100,000 – $110,000 Role Overview Ocean Advisor is seeking a dedicated Data Technologist to serve as the vital link between our maritime clients and our engineering team. Much like a Petroleum Technologist in the oil and gas industry, your primary mission is "Data I/O" - managing the intake, sanitization, and organization of critical client data to ensure it is ready for high-level analysis and system integration. This is a role for a "Data Purist" - someone who finds genuine satisfaction in transforming messy, real-world datasets into clean, structured assets. If you love the "nitty-gritty" of data work and enjoy collaborating with both clients and technical teams, this is your ideal environment.

Key Responsibilities

Data Intake & Management:

Act as the primary point of contact for clients sending over raw data (CSVs, spreadsheets, and manual reports).

Data Sanitization:

Review, clean, and reformat client data to meet internal engineering standards, ensuring accuracy and consistency.

Engineering Collaboration:

Work closely with the software engineering team to organize data structures and ensure seamless "stitching" of sensor and client information.

Pipeline Coordination:

Manage and implement the flow of data through internal systems and tracking tools to ensure no information is lost or delayed.

Quality Assurance:

Identify anomalies or errors in raw data and communicate directly with clients to resolve discrepancies. Required Qualifications

Experience:

3–5 years of experience in a data-centric role (Data Technician, Petroleum Technologist, or Data Coordinator).

Technical Literacy:

Proficient in Excel and CSV manipulation.

SQL Knowledge:

Familiarity with SQL and basic database concepts is highly preferred to assist in data organization.

Education:

Associate’s degree or professional diploma. We value practical experience and a steady hand over high-level academic theory.

Soft Skills:

High attention to detail and strong communication skills. You must be comfortable explaining data requirements to clients and technical requirements to engineers.