Senior Data Engineer

4 weeks ago

Johannesburg, Gauteng, South Africa Entelect Software Ltd Full time

Transform Your Career with Entelect


Elevate your skillset as a Senior Data Solutions Engineer at Entelect, where we foster a culture of growth, collaboration, and innovation. Our dynamic, multidisciplinary environment encourages versatility and provides individual attention to career development, including regular one-on-ones with leadership.



Key Responsibilities

  • Delivery: Seamlessly integrate big data from multiple sources into a reliable, evolving asset, working closely with Solution Architects to design and implement cloud, hybrid, and on-prem solutions.
  • Design and Implementation: Develop optimal data pipelines and deliver impactful advanced analytics using ML, AI, cognitive services, and data science, covering descriptive, diagnostic, predictive, and prescriptive analytics.
  • Data Science and Engineering: Familiarize yourself with ML algorithms and AI approaches, including clustering, regression, classification, speech recognition, OpenAI, LLMs, vision, search, and translation, and ensure continuous deployment in short cycles with maximum impact and high quality.
  • Metadata and Data Lineage: Maintain data lineage and metadata effectively, and design and develop business dashboards.
  • Customer-Facing: Build strong relationships and understand customer needs to deliver impactful solutions, and ensure compliance with data security and industry regulations.


What You'll Get from Us

  • 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 Africa's most esteemed organisations.


What to Expect from the Recruitment Process

Our aim is to make the recruitment process as efficient as possible, keeping you informed every step of the way. The first step is an initial conversation with our talent team to get to know you better and introduce you to Entelect and all that we have to offer. The next step will be a 1.5-hour in-person technical interview at one of our offices where you will meet some of our leadership team. Finally, if we are both aligned, we wrap up the process with salary discussions and present you with an offer of employment.



Requirements

  • A bachelor's 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.

Tech Stacks We Use:



  • 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

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