Intermediate BI Data Analyst

About the Company

We help our clients understand the rich data we collect from the traditional retail market in South Africa and Africa broadly. The ideal candidate will have a strong analytical and mathematical background to help drive value from our data. This person will wear many hats in the role, but much of the focus will be on building out our Python ETL processes and writing superb SQL. In addition, the candidate will be responsible for maintaining and building out our reporting DB. Beyond technical prowess, the data engineer will need soft skills for clearly
communicating highly complex data trends to organizational leaders and to clients. We’re looking for someone willing to jump right in and make an impact in the traditional retail market through powerful data pipelines.

About the Role

Typically, generate insight and logic through our unique informal market data asset whilst establishing and implementing the analytical models required to enrich and automate our insights that improve our responsiveness and understanding of the data. To establish deep routed understanding in the data to drive strategy that fundamentally overhauls our decision-making processes based on logic and insight. Aligning our own data with external data sets that can enrich our understanding of the data is also required to draw correlations and market insights that are predictable. Through this understanding, commodify the data into easy-to-understand reports and dashboards aligned to our client’s needs.

Key Responsibilities

Work closely with our development team, data analysts and BI analysts to help build and maintain data flows that support our reporting requirements.
Use agile software development processes to make iterative improvements to our back-end systems, particularly our reporting DB.
Model front-end and back-end data sources to help draw a more comprehensive picture of user flows throughout the system and to enable powerful data analysis.
Build data pipelines that clean, transform, and aggregate data from disparate sources and deliver quality usable data to data analysts and BI analysts for reporting.
Develop models that can be used to make predictions and answer questions for the overall business.
Data Processing & Management

Gathering/Extracting data from the database for analysis.
Cleaning and preparation of data for analysis.
Quality controlling our data processes and tables.
Identify, analyse, and interpretation of market data for clients.
Producing accurate BI reports & Dashboards, within agreed upon timeframes, which are:
Data valuable
Understandable to both a technical and non-technical audience
Insightful and supports quality decision making for internal and external stakeholders
Create project tracking reporting for all stakeholders.
Setting up processes and systems to make working with data more efficient.
Exploring and interpreting data to identify trends and opportunities for business improvement.
Identifying data shortcomings and alerts within campaigns to drive proactive responses.
Provide recommendations on campaign performance improvements, based on client data and industry standards.
Researching new ways to make use of data, to improve business performance.
Managing the team to ensure that quality deliverables are produced timeously
Stakeholder Engagement

Responding timeously to data-related requests and queries and keeping track of all requests.
Collaborating with key stakeholders on all aspects of report creation, incl. deadlines, deliverables, edits, recommendations.
Scoping out the required data models required to drive efficiency with stakeholder buy-in.
Attending meetings with internal & external stakeholders to ensure understanding of the project data and requirements.
Presenting information and communicating findings generated from data to stakeholders, suited to a technical and non-technical audience.
Candidate Requirements

Required Skills and Qualifications

Bachelor’s degree in computer science, information technology, engineering, or related analytical discipline required.
Three or more years of experience with Python, SQL, and data visualization/exploration tools (Power BI, Tableau etc).
Familiarity with common python based ETL tools such as PySpark or Apache Airflow.
Familiarity with Kimball & Inmon data warehousing approaches.
Familiarity with the AWS ecosystem, specifically Redshift, RDS & EC2.
Familiarity with PostgreSQL preferred.
Communication skills, especially for explaining technical concepts to nontechnical business leaders.
Ability to work on a dynamic, results-oriented team that has concurrent projects and priorities