DataDivers - Senior Data Engineer

DataDivers is hiring! 

DataDivers, part of the Rmkble family, is on the hunt for a dynamic and driven Senior Data Engineer to join our growing team. 

About DataDivers 

DataDivers is one of Rmkble's specialist businesses, dedicated to all things data and analytics. Our expertise spans data strategy, data platforms, DataOps, advanced analytics, data science and AI, and building a data culture in our clients’ organisations. We are exceptional problem solvers who turn data into real business insights. 

As a results-driven organisation, we are committed to remarkable outcomes for our clients. We are well-known for always delivering, but not only do we deliver, we go above and beyond to exceed expectations and build lasting relationships. We don’t operate in isolation to achieve this; we have strong partnerships with Microsoft, Snowflake, AWS, Databricks and Informatica, to name a few. 

With a diverse client base, our people work across an exciting mix of organisations and with a variety of technology stacks. Our clients are both local and international, in the public and private sectors, and cover a vast cross-section of different domains, from health to government to mining to not-for-profits. 

Our people are second to none in their field. They are true experts who are continuously learning and continuously giving back. Some deliver learning and mentoring programs; others are shaping future products, or tweaking frameworks and tools to advance new thinking. At the heart of what sets DataDivers apart is the support that our leaders and our people give to each other.  

We believe that passion and curiosity lead to awesome possibilities for both you and for us. So come join the team and have a remarkable journey! 

About the role

 A Senior Data Engineer is a specialist role within the DataDivers business. This role possesses significant ICT technical expertise in one or more areas such as data engineering, data analysis, data manipulation and data visualisation. Data Engineers often lead teams in developing data solutions for client to meet their unique needs relating to understanding the data managed within their business. The role is primarily responsible for the design and implementation of data engineering solutions.  

A Senior Data Engineer is responsible for understanding the client’s data needs, assessing the quality of the client’s data, using the data to provide client insights and present views on how that insight can bring benefit to the client’s organisation.  A Senior Data Engineer at DataDivers facilitates lasting sustainability for their clients through the delivery of pragmatic solution outcomes.  

Commonly, the Senior Data Engineer is required to lead a team of data engineers. In this role, they are responsible for ensuring the team members understand their role, manage the status of delivery, manage client relationships and communication, and provide support to more junior team members if required. 

Key Responsibilities:  

Data Architecture Design: 

• Design and implement data models and architectures that support business needs. 

• Evaluate and select appropriate data storage solutions (e.g., databases, data lakes, lakehouses). 

ETL Development: 

• Build and optimize Extract, Transform, Load (ETL or ELT) processes for data integration from various sources. 

• Ensure data quality and integrity throughout the ETL or ELT pipeline. 

Data Pipeline Management: 

• Create and manage data pipelines to ensure timely and efficient data flow. 

• Monitor and troubleshoot pipeline performance and data anomalies.  

Collaboration: 

• Work closely with data scientists, analysts, and stakeholders to understand data requirements. 

• Provide technical guidance and mentorship to junior data engineers. 

Data Governance: 

• Implement data governance best practices to ensure compliance and data security. 

• Maintain documentation of data sources, pipelines, and architecture.  

Performance Optimization: 

• Analyse system performance and make recommendations for improvements. 

• Optimize data storage and processing to reduce costs and improve efficiency. 

 Technology Evaluation: 

• Stay current with emerging technologies and industry trends related to data engineering. 

• Evaluate and recommend new tools and technologies to enhance data capabilities. 

Skills

• Extensive experience in IoT architectures and ETL/ELT frameworks (Very High)
• Understanding of data modelling and database design principles (Very High)
• Ability to interpret technical requirements and translate into technical solutions and architectures (Very High)
• Extensive experience in deploying production‑ready data pipelines (Very High)
• Communication and collaboration (Very High)
• Skills Framework for the Information Age (SFIA) – https://sfia-online.org/en (High)
• Business consulting experience (High)
• Conceptual thinking (High)
• Leadership and relationship management (High)
• Problem‑solving and trouble‑shooting (High)

Tools / Languages (Highly Proficient)

• Experience with Microsoft ADF, AWS Glue, AWS Lambda, Fivetran, DBT, Talend, Informatica, and other ETL/ELT tools
• Experience with one of AWS Redshift, Snowflake, Azure Synapse, Azure SQL, Microsoft SQL, Oracle, PostgreSQL, or MySQL
• Experience coding in SQL
• Proficiency in coding with Python, R, or similar
• Experience using cloud platforms including Azure, Snowflake, AWS, and GCP, as well as Kubernetes, Docker, and similar

Methodologies (Proficient)

• Extensive experience with Data Warehousing methodologies (e.g., Ralph Kimball, Data Vault)
• Broad understanding of CI/CD practices in Azure, AWS, or GCP
• Experience of data quality and data governance processes to ensure data accuracy and reliability

Experience: 

• At least 5 years’ experience in a similar role. 

• At least 5 years’ experience in client delivery within a project / consultancy environment. 

• Considerable experience in a leadership role(s) managing design and delivery of data solutions. 

Specific Qualifications: 

The Rmkble Data Engineer Senior) should have the following minimum qualifications: 

• Undergraduate university degree in Computer Science / Statistics, Mathematics, Science, Engineering or Technology. 

• Masters level degree preferred.