Junior Data Analyst

Trade Ocean South Africa; Wes-Kaap; On-site; ZAR 210,000 - 270,000; Full time

Job summary

Trade Ocean Shared Services in Cape Town seeks a Junior Data Analyst within Business Improvement on a nine-month fixed-term contract. You will own hands-on data cleansing, reformatting, and enrichment to meet master data standards, using Excel, Power Query and SQL, while obtaining missing data from busy operational and finance managers.

You will turn messy datasets into clean, reliable tables, ensuring accuracy and repeatability through documented cleansing rules and automation.

Qualifications

• A diploma or bachelor's degree in Information Systems, Data Science, Business Analytics or a related field.
• One to two years in a data-related role such as data capturing, data cleaning, business analysis or similar is advantageous.
• Prior exposure to software implementation, ERP migration or large-scale data-cleanup projects is advantageous.
• Advanced Excel is non-negotiable, including XLOOKUP, INDEX/MATCH, complex nested formulas, text manipulation, pivot tables and data validation.
• Strong proficiency in Excel Power Query for automating the cleaning and merging of large datasets is non-negotiable.
• Working knowledge of SQL, covering joins, filtering, aggregation and basic scripting, is non-negotiable.
• Demonstrated high attention to detail and accuracy on large datasets is non-negotiable.
• A methodical, organised temperament that sustains quality through repetitive, high-volume work is non-negotiable, as is confident, assertive communication with busy operational and finance managers.

Responsibilities

• Cleanse and standardise records to conform to master data standards.
• Extract and profile data from source systems and identify quality issues.
• Enrich records to meet completeness thresholds.
• Build repeatable Power Query and SQL routines to automate cleaning.
• Reconcile data across source systems and resolve discrepancies.
• Document cleansing rules and transformation logic for repeatability.
• Log and escalate data issues and provide ad hoc support to the department.
• Spot anomalies, duplicates and data faults and raise them to the lead.
• Secure missing data and approvals from managers.
• Deliver target datasets to the golden system of record.
• Handover documented cleansing methods at contract end.

Skills

Detailing

Excel advanced

Power Query

SQL

Data cleaning

Data profiling

Communication with managers

Education

Diploma/Bachelor's in Information Systems/Data Science/Business Analytics

Tools

Excel

Power Query

SQL

Job description

Trade Ocean is a Southern African maritime and logistics group established in 2007. We specialise in Customs Clearing, Freight Forwarding and Ships Agency services, operating across six branches from Cape Town to Walvis Bay, connecting clients to a global network. Our culture is built on a simple but powerful foundation: taking ownership, and we are always looking for people who do the same.

As Junior Data Analyst in Business Improvement at Trade Ocean Shared Services in Cape Town, you will report to the Process and Data Lead on a nine-month fixed-term contract. You will own the hands-on work of finding data quality problems, cleansing and reformatting records, and enriching datasets so that they conform to agreed master data standards. This is a high-volume execution role rather than a modelling, dashboarding or data science one, so expect long stretches in Excel, Power Query and SQL, working through large and often messy datasets with care. You will also need to be comfortable approaching busy operational and finance managers to secure the missing data and approvals you need to finish the job. If you take genuine satisfaction in turning a broken spreadsheet into a clean, reliable table, you will find plenty of that here.

QUALIFICATION AND EXPERIENCE:

• You hold a diploma or bachelor's degree in Information Systems, Data Science, Business Analytics or a related field, although relevant work experience will be considered in lieu of a formal qualification.
• One to two years in a data-related role such as data capturing, data cleaning, business analysis or similar is advantageous.
• Prior exposure to software implementation, ERP migration or large-scale data-cleanup projects is advantageous.
• Advanced Excel is non-negotiable, including XLOOKUP, INDEX/MATCH, complex nested formulas, text manipulation, pivot tables and data validation.
• Strong proficiency in Excel Power Query for automating the cleaning and merging of large datasets is non-negotiable.
• Working knowledge of SQL, covering joins, filtering, aggregation and basic scripting, is non-negotiable.
• Demonstrated high attention to detail and accuracy on large datasets is non-negotiable.
• A methodical, organised temperament that sustains quality through repetitive, high-volume work is non-negotiable, as is confident, assertive communication with busy operational and finance managers.

JOB REQUIREMENTS:

• Cleanse and standardise records so that they conform fully to the agreed master data standards.
• Extract and profile data from source systems and identify quality issues before they reach the project team.
• Enrich records and complete golden record attributes so that datasets meet agreed completeness thresholds.
• Build repeatable Power Query and SQL routines that replace manual cleaning and reduce rework cycle time.
• Reconcile and cross-reference data across source systems so that discrepancies are identified and resolved.
• Document cleansing rules, transformation logic and standards well enough for another analyst to repeat the work.
• Log, track and escalate data issues rather than silently patching them, and provide ad hoc support to the department.
• Spot anomalies, duplicates and systemic data faults early and raise them with the Process and Data Lead.
• Secure missing data and approvals from operational and finance managers without needing to be chased yourself.
• Sustain agreed throughput volumes without quality drift or shortcuts as datasets grow.
• Deliver target datasets migrated to the golden system of record against agreed accuracy and completeness thresholds.
• Hand over a documented, repeatable cleansing method at the end of the contract.

KEY ATTRIBUTES:

• Detail Obsession: You take pride in turning a chaotic, broken spreadsheet into a flawless data table, catching errors before anyone else sees them.
• Consistent Throughput: You keep high volumes of repetitive cleansing moving without letting quality slip or taking shortcuts.
• Tooling Leverage: You look for ways to move from manual cleaning to repeatable Power Query and SQL routines.
• Pattern Recognition: You notice anomalies, duplicates and systemic data faults early and escalate them rather than quietly patching over them.
• Assertive Follow-Through: You chase busy operational and finance managers for missing data and approvals until you have what you need.
• Autonomy Within Standards: You work independently once the standards are clear, and raise ambiguity proactively instead of assuming.
• Documentation Discipline: You write down cleansing rules and transformation logic so that another analyst could repeat your work exactly.