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.