Cloud Data Engineering Leader
2 days ago
We are looking for a seasoned data engineer to join our team at Confiz, where you will be responsible for expanding and optimizing our big data pipelines. Collaborative problem-solving, sophisticated design, and the creation of quality products are essential in this role.
Key Responsibilities- We require a skilled data engineer who can work alongside our Big Data Solution Architects to design, prototype, implement, and optimize data ingestion pipelines, ensuring seamless data sharing across various business systems.
- You will build ETL/ELT Ingestion pipelines and analytics solutions using cloud and on-premises technologies.
- The successful candidate will ensure that the design, code, and procedural aspects of the solution meet production-ready standards, focusing on operational, security, and compliance requirements.
- As part of our team, you will participate in day-to-day project and production delivery status meetings, providing technical support for faster issue resolution.
- A Bachelor's degree from an accredited college/university or equivalent work experience is required.
- The ideal candidate will have 5+ years of experience performing data engineering, warehousing, publishing, and visualization throughout the full data lifecycle.
- At least two (2) years of experience as an Azure Data Engineer or in a similar role in a technology or IT consulting environment is necessary.
- We seek candidates with 3 years of experience in data profiling, cataloguing, and mapping to enable the design and build of technical data flows.
- Experience defining ELT/ETL architecture and process design is also essential.
- The successful candidate will have 2 years of experience performing end-to-end implementation of data warehousing analytics solutions built on MS or Azure platforms.
- A minimum of 2 years of experience working with Azure is required.
- Candidates should have experience creating data pipelines using ETL tools like Airflow, ADF.
- Experienced individuals in distributing computing technologies like Apache Spark, Databricks are also preferred.
- Stream-processing systems like Spark Streaming, Eventhub are also relevant to this role.
- Proficiency in one of the object-oriented and functional languages: Python, Java, Scala, etc., is necessary.
- Experience writing effective and maintainable unit and integration tests for ingestion pipelines is required.
- Using static analysis and code quality tools is also expected.
- Familiarity with code version control repositories like Git is necessary.
- Security best practices including encryption of sensitive data, encryption at rest, and encryption in flight are critical.
- Building CI/CD pipelines & DevOps orchestration tool like Jenkins is also essential.
- Familiarity with Data Lakehouse, Delta Lake, Apache Hudi is beneficial.
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