Analytics Engineer

SUMMARY:
Are you an experienced and skilled Analytics Engineer looking for a new opportunity?

POSITION INFO:
Job & Company Description:

Seeking an Analytics Engineer for a mining concern in the northern suburbs on a contractual basis of 6 months. The analytics engineer makes sure data is ingested, transformed, scheduled, and ready to be used for analytics. They are responsible for designing, implementing, and maintaining data pipelines, analytics systems, and reporting solutions. The analytics engineer also models raw data into clean, tested, and reusable datasets to allow business stakeholders to view and understand data in a warehouse or database.

Key performance areas include:

• Delivers well-defined, transformed, tested, documented, and code-reviewed datasets for analysis
• Builds data aggregation pipelines using Python, Apache Airflow, Spark, SQL, or ClickHouse
• Creates robust data models and architectures to support analytics initiatives
• Collaborates with business stakeholders to understand their analytics needs and deliver comprehensive reports, dashboards, and models
• Identifies and implements optimizations to continually enhance query performance, reduce processing time, and increase overall productivity
• Designs, develops and maintains data pipelines to ensure efficient and reliable ETL processes
• Implements and maintains analytics systems, data warehouses, or data lakes to store and manage structured and unstructured data

• A master’s degree in computer science, data science, software engineering, or related field

• At least five years of experience in data analytics, data engineering, software engineering, or a similar role
• Expertise in data modelling, ETL development, and data analysis

• Strong ability in SQL for data extraction and manipulation, and proficiency in data warehousing concepts/tools such as Redshift and Snowflake
• Familiarity with cloud-based data platforms such as AWS, GCP, and Azure for data storage and processing
• Substantial programming ability using languages/tools such as R, Python, JavaScript, Scala, and C++ for data manipulation and scripting
• Solid understanding of relevant data governance, data quality, and data security best practices
• Knowledge of ETL processes, data integration, and data warehousing concepts
• Familiarity with data visualization tools such as Tableau, Power BI, and Looker
• Knowledge of big data technologies and distributed computing frameworks such as Hadoop and Spark