Senior Data Solutions Engineer

Exciting Opportunity for a Senior Data Solutions Engineer

Elevate your career, where we prioritise people and nurture a culture of growth, collaboration, and innovation.

Join a dynamic, multidisciplinary environment that encourages versatility, and provides individual attention to career development, including intentional and regular one-on-ones with leadership.

Tackle complex challenges and make a meaningful impact alongside passionate professionals who inspire and support each other.

DELIVERY

• →Wrangling big data from multiple sources into a reliable, evolving asset.
• →Collaborating with Solution Architects to design and implement cloud, hybrid, and on-prem solutions.
• →Designing and implementing optimal data pipelines and delivering impactful advanced analytics using ML, AI, cognitive services, and data science.
• →Working across descriptive, diagnostic, predictive, and prescriptive analytics.
• →Familiarising yourself with ML algorithms and AI approaches, including clustering, regression, classification, speech recognition, OpenAI, LLMs, vision, search, and translation.
• →Understanding DataOps and MLOps to ensure continuous deployment in short cycles with maximum impact and high quality.
• →Maintaining data lineage and metadata effectively.
• →Designing and developing business dashboards.
• →Using technical and data analytics expertise to improve business innovations.

people

• →Demonstrating maturity, motivation, and leadership in the workplace.
• →Championing change within the team and fostering a collaborative culture.
• →Collaborating with cross-functional teams to tackle complex business challenges, driving continuous improvement.
• →Mentoring and nurturing colleagues to uphold standards of excellence and accountability.

Customer

• →Building strong relationships and understanding customer needs to deliver impactful solutions.
• →Managing customer expectations and identifying opportunities for service improvements.
• →Ensuring compliance with data security and industry regulations.

• →A competitive compensation package with twice-yearly salary increases and guaranteed bonuses.
• →Tenure-based loyalty leave.
• →Access to employee wellness programs and rewards for professional development.
• →Commission incentives for successful business development leads and employee referrals.
• →Hands-on support from leadership through regular one on ones and quarterly reviews.
• →Continuous development programs offering training in leadership and technical skills.
• →Exposure to enterprise projects across multiple domains and problem spaces for South Africas most esteemed organisations.

• A bachelors degree in IT, Engineering, or related fields.
• Minimum 6 years experience as a data solutions engineer in an enterprise environment.
• Proficiency in software engineering fundamentals and commitment to clean code and best practices.
• Experience working in a delivery team together with other disciplines to deliver a product.
• Strong ability to model and analyse data.
• Solid understanding of data engineering methodologies.
• Good understanding of visualisation best practices.
• A desire to design and implement modern advanced analytics solutions and modern data warehousing solutions.
• Strong collaboration and communication skills with a drive for continual improvement.
• Pro hybrid working model working from the office on average 2 – 3 times per week.
• A strong customer-facing ability.
• Flexibility to work across a variety of different environments and tooling.

*Popular but not limited to

• Cloud environments: Azure, AWS, Google
• Front-end tech: Power BI, Microsoft Fabric, Amazon Quicksight, Google Data Studio, Grafana
• Languages: SQL, Python, Scala
• Data processing: Azure Data Factory, Amazon Glue, Apache Airflow, Databricks, Spark SQL
• Relational databases: MSSQL, PostgreSQL, Oracle, MySQL, Azure SQL, Amazon RDS
• NoSQL databases: MongoDB, Cosmos DB, DynamoDB, Neo4j
• Streaming: Azure Stream Analytics, Kafka, Databricks streaming, Spark streaming, Google Dataflow, Amazon Kinesis
• ML Platforms: Azure Machine Learning, Databricks ML, Amazon Sagemaker, Dataiku
• AI: Azure OpenAI, Azure Cognitive Services, AWS Cognitive Services, Google Cognitive Services