Senior Data Engineer/Analyst

Boardroom Appointments; Johannesburg; On-site; ZAR 800,000 - 1,200,000; Full time

Job summary

A recruitment firm is looking for a Senior Data Engineer/Analyst based in Johannesburg, South Africa. The successful candidate will design and maintain ETL pipelines, optimize data warehouses, and ensure data quality across workflows. They should have over 5 years of experience in data engineering, strong skills in SQL and Python, and familiarity with cloud platforms like AWS or Azure. The role involves collaboration with data teams and providing actionable insights through data analysis and visualization tools.

Qualifications

• 5+ years of experience in data engineering, analytics, or BI development.
• Strong proficiency in SQL and Python for data manipulation and transformation.
• Experience with ETL/ELT processes, data modeling, and data warehousing concepts.

Responsibilities

• Design, develop, and maintain scalable ETL pipelines for data ingestion.
• Build optimized data warehouses to support business intelligence needs.
• Ensure data quality and integrity across data processing workflows.

Skills

SQL

Python

Data engineering

Business Intelligence (BI)

Data visualization (Power BI, Tableau)

Education

Bachelor's or Master's in Computer Science, Data Science, Engineering, Mathematics

Tools

AWS

Azure

Google Cloud Platform (GCP)

Apache Spark

Snowflake

Databricks

Kafka

Job description

About the job Senior Data Engineer/Analyst

Qualifications & Experience:

Must-Have:

Bachelors or Masters degree in Computer Science, Data Science, Engineering, Mathematics, or a related field.

5+ years of experience in data engineering, analytics, or BI development.

Strong proficiency in SQL and Python for data manipulation and transformation.

Experience with ETL/ELT processes, data modeling, and data warehousing concepts.

Expertise in cloud platforms (AWS, Azure, or GCP) and big data tools (Spark, Snowflake, Databricks, Kafka).

Familiarity with data visualization tools (Power BI, Tableau, Looker).

Nice-to-Have:

Experience with AI/ML model deployment for predictive analytics.

Knowledge of DevOps for data (CI/CD, Infrastructure-as-Code).

Certifications in AWS Data Analytics, Azure Data Engineer, or Google Cloud Professional Data Engineer.

Responsibilities:

Data Engineering & Architecture:

Design, develop, and maintain scalable and efficient ETL pipelines for data ingestion, transformation, and storage.

Build and optimize data warehouses, data lakes, and real-time streaming solutions to support business intelligence and analytics needs.

Ensure data quality, integrity, and security across all data processing workflows.

Collaborate with Data Scientists, Analysts, and Software Engineers to design data models that enable advanced analytics.

Implement data governance, cataloging, and lineage tracking to ensure transparency and compliance.

Conduct data exploration, statistical analysis, and trend identification to extract actionable insights.

Develop interactive dashboards and reports using BI tools like Power BI, Tableau, or Looker.

Work closely with business teams to understand KPIs and performance metrics, translating data into valuable insights.

Optimize query performance and database efficiency for large-scale data processing.

Design and manage cloud-based data solutions (AWS, Azure, GCP) with services such as AWS Glue, Azure Data Factory, Google BigQuery, Snowflake, and Databricks.

Work with big data frameworks like Apache Spark, Hadoop, or Kafka for distributed data processing.

Develop automated data pipelines using orchestration tools like Airflow, Prefect, or Luigi.

Work cross-functionally with engineering, product, and business teams to define data requirements.

Mentor junior team members and provide guidance on best practices in data engineering and analytics.

Drive continuous improvement initiatives in data architecture, automation, and AI-driven analytics.