Intermediate Analytics Engineer - Banking - Contract 6 months

Losika Consulting; Sandton; In loco; ZAR 600.000 - 800.000; Tempo pieno

Descrizione del lavoro

Losika Consulting is looking for an Intermediate Analytics Engineer in Johannesburg to build trusted data products that enable enterprise decision-making. This hybrid role involves collaborating with a high-performing data team to design scalable analytical solutions for a leading financial institution.

As an Analytics Engineer, you will work on large enterprise data platforms, turning raw data into trusted analytical assets that drive business intelligence initiatives.

The position requires strong SQL skills and experience with ETL/ELT processes, making it essential for a candidate eager to influence data governance and quality.

Competenze

• 3–6 years' experience in Analytics Engineering, Data Engineering or Data Modelling.
• Experience building and maintaining ETL/ELT data pipelines.
• Ability to translate business requirements into technical data solutions.

Mansioni

• Designing, building and maintaining scalable analytical data models.
• Developing reliable, reusable and well-documented data products.
• Optimising SQL queries and pipeline performance.

Conoscenze

Strong SQL development skills

Data Profiling

ETL/ELT development

Experience designing analytical data models

Data Governance

Dimensional Modelling

Data Quality

Formazione

Degree in Computer Science

Strumenti

Azure Data Factory

Databricks

Synapse Analytics

APIs

Git

Descrizione del lavoro

Intermediate Analytics Engineer

Build trusted data products that power enterprise decision-making

Location: Johannesburg (Hybrid)
Employment Type: Contract

About the Opportunity

A leading South African financial institution is expanding its modern data and analytics capability and is looking for an experienced Intermediate Analytics Engineer to join a high-performing data team.

This is an opportunity to work on large-scale enterprise data platforms where your work will directly enable advanced analytics, reporting, AI initiatives and self-service business intelligence across multiple business domains.

You’ll work alongside Data Engineers, Architects, Data Modellers, Governance specialists and business stakeholders to design trusted, analytics-ready datasets that become the foundation for strategic business decisions.

If you enjoy solving complex data challenges, building scalable data products and creating clean, reliable data that people actually trust, we’d love to hear from you.

What You’ll Be Doing

As an Analytics Engineer, you will bridge the gap between data engineering and business analytics by transforming raw enterprise data into trusted, reusable and well-governed analytical assets.

• Designing, building and maintaining scalable analytical data models
• Developing reliable, reusable and well-documented data products
• Building and optimising data pipelines across multiple enterprise source systems
• Translating business requirements into analytics-ready datasets
• Creating conceptual, logical and dimensional data models
• Performing data profiling, validation, reconciliation and quality assessments
• Defining data contracts, business rules and metadata
• Implementing data lineage and ensuring governance standards are maintained
• Optimising SQL queries, pipeline performance and cloud processing costs
• Collaborating with Data Engineers, Architects, Governance teams and business stakeholders
• Supporting self-service analytics through trusted semantic data models
• Monitoring data quality, pipeline health and production performance
• Mentoring junior Analytics Engineers and contributing to engineering best practices

What We’re Looking For

We’re looking for someone who combines strong technical capability with excellent analytical thinking and stakeholder engagement.

Essential Experience

• 3–6 years' experience in Analytics Engineering, Data Engineering or Data Modelling
• Strong SQL development skills
• Experience designing analytical data models
• Experience building and maintaining ETL/ELT data pipelines
• Data profiling, cleansing and validation experience
• Strong understanding of enterprise data architecture
• Experience working with structured and semi-structured data
• Ability to translate business requirements into technical data solutions
• Experience working within enterprise data governance frameworks

Technical Skills

You’ll have experience with many of the following:

• Advanced SQL
• Data Modelling
• Dimensional Modelling
• Data Vault 2.0
• Relational Database Design
• ETL / ELT Development
• Data Quality
• Metadata Management
• Data Lineage
• Data Governance
• Azure Data Platform
• Azure Data Factory
• Databricks
• Synapse Analytics
• APIs
• Git
• CI/CD concepts
• Cloud Data Platforms

You’ll Stand Out If You Have

• Financial services or enterprise-scale data experience
• Experience building governed data products
• Strong understanding of semantic modelling
• Exposure to self-service analytics platforms
• Experience improving performance and reducing cloud processing costs
• Knowledge of modern data architecture principles
• Passion for mentoring and knowledge sharing
• Fleet experience

Qualifications

• Degree in Computer Science, Information Systems, Data Science, Engineering or a related field

Success in This Role

The successful candidate is someone who:

• Thinks analytically and enjoys solving complex data problems
• Builds high-quality, scalable data solutions
• Takes ownership and delivers consistently
• Has exceptional attention to detail
• Works collaboratively across technical and business teams
• Is passionate about data quality and governance
• Continuously looks for ways to improve automation, efficiency and performance

Why Apply?

This is an opportunity to join one of South Africa’s most advanced enterprise data environments, working with modern cloud technologies and large-scale data platforms that support business-critical decision-making.

You’ll be part of a collaborative, highly skilled team where you’ll have the opportunity to influence how enterprise data is designed, governed and consumed while working on projects that have real business impact.