Data Engineer (Python, SQL, PySpark, over $30K)

• Few vacancies

• Listed company

• Good working environment
  

Main Responsibilities

• Manage Cloud Platform: Maintain and optimize our Azure and Databricks cloud data platform to run smoothly at scale.

• Deliver Platform Projects: Work with external vendors from design to rollout on cloud platform upgrade projects.

• Build Models & Dashboards: Partner with Data Analysts to clean data, build efficient data models, and create Power BI dashboards.

• Test New Tools: Run quick proofs-of-concept (PoCs) to test new cloud data tools and features.

• Test Pipelines: Verify data flows, schemas, and performance so solutions meet business needs.

• Automate Workflows: Write automation scripts and runbooks to simplify deployment, monitoring, and fixes.

• Maintain Documentation: Document pipeline architecture and setup steps for smooth handoffs to internal teams.
  

Requirements

• Bachelor’s degree in Computer Science, Information Technology, Data Science, or a related quantitative field.

• Hold a recognized cloud data platform certification (such as Azure Data Engineer Associate) is preferrable 

• Have at least 3 years of hands-on professional experience building and managing cloud data platforms.

• Be proficient in Python, SQL, PySpark, Azure Data Factory, ADLS Gen2, Databricks, Unity Catalog, Power BI, and event messaging tools like Kafka or Event Hubs, with a strong understanding of standard software development practices (SDLC).

• Understand core data governance principles and the data lifecycle, including data quality, lineage, security, and compliance.

• Demonstrate strong analytical and problem-solving skills, self-motivation, clear communication, and a collaborative team attitude.