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Data Engineering Specialist
2 weeks ago
Blue Bean Software is a leading custom software and product development company that partners with both large enterprises and dynamic start-ups to solve their most complex challenges. With a flat organisational structure, we empower every team member to make an impact and deliver exceptional customer service.
Job Description
We are seeking skilled Data Engineers to join our talent pool for future opportunities. By submitting your details, you can be pre-vetted for roles where you can design, build, and manage robust data pipelines and infrastructure. Your expertise will enable organisations to harness the power of data, driving insights and innovation.
Key Responsibilities
- Design, develop, and maintain scalable data pipelines to process and transform large volumes of data.
- Integrate data from various sources, ensuring data quality, consistency, and reliability.
- Optimise data storage and processing for performance, scalability, and cost efficiency.
- Collaborate with data scientists, analysts, and business stakeholders to support data-driven decision-making.
- Implement and manage big data platforms and tools such as Hadoop, Apache Spark, and Kafka.
- Ensure data security, compliance, and governance across all data processes.
- Monitor and troubleshoot data pipelines to ensure smooth operation and minimal downtime.
- Stay updated with the latest trends and technologies in data engineering and big data.
Your Skills and Experience
To excel in this role, you will need:
- Proven experience as a Data Engineer or in a similar role.
- Strong proficiency in big data tools and frameworks (e.g., Hadoop, Apache Spark, Kafka, Apache Flink).
- Expertise in programming languages such as Python, Java, Scala, or SQL.
- Experience with ETL/ELT processes and tools (e.g., Talend, Informatica, Apache NiFi).
- Familiarity with cloud-based data solutions and services, including AWS (Redshift, Glue, EMR, S3), Azure (Synapse, Data Factory, Databricks), Google Cloud (BigQuery, Dataflow, Pub/Sub).
- Knowledge of database systems, including relational databases (e.g., PostgreSQL, MySQL, SQL Server), NoSQL databases (e.g., MongoDB, Cassandra, DynamoDB), data warehousing solutions (e.g., Snowflake, Redshift, BigQuery).
- Experience with data modeling, data architecture, and data governance best practices.
- Familiarity with workflow orchestration tools like Apache Airflow or Luigi.
- Strong understanding of data security, compliance, and privacy regulations (e.g., POPIA, GDPR).
- Knowledge of containerisation and orchestration tools (e.g., Docker, Kubernetes) is a plus.
- Experience with version control systems (e.g., Git) and CI/CD pipelines.
- Strong problem-solving skills and attention to detail.
- Excellent communication and collaboration skills.
- Relevant certifications (e.g., AWS Certified Data Analytics, Google Cloud Data Engineer, Azure Data Engineer Associate) are a plus.