Position: Data Engineer
Company: Aspire Global
Category: Data Engineer
Experience required: 3y
English level: upper
Published: 2022-09-01T00:00:00+03:00

Requirements

•  3+ years of experience in Data Engineering;
• Degree in Computer Science, Software Development or Engineering;
• Proficient in Python. Past exposure to Java will be considered an asset;
• Understanding of RDMS, Columnar and NoSQL engines & performance;
• Experience with cloud architecture and tools: Microsoft Azure, Amazon or GCP;
• Strong background in stream data processing technologies such as NiFi, Kinesis, Kafka;
• Experience with orchestration tools such as Apache AirFlow, dbt;
• Prior exposure to the Snowflake ecosystem will be considered an asset;
• Familiarity with DevOps methodologies and concepts;
• Understanding of distributed logging platforms — ideally the ELK stack.

Skills Requirements
•  Fluency in spoken and written English is essential;
• Passionate about data and on the lookout for opportunities to optimise;
• Passionate about technology and eager to recommend new platforms.

We Offer

•  High-level compensation and regular performance-based salary and career development reviews;
• PE accounting and support;
• Working remotely;
• Medical insurance (health), employee assistance program;
• 20 working days of paid vacation; paid holidays, and sick leaves;
• Sport compensation;
• English classes with native speakers, training, conferences participation;
• Referral program;
• Team buildings, corporate events.

Responsibilities

•  Create data pipelines to ingest data from dissimilar sources (performance, reliability, monitoring);
• Serve data models as a product to the entire organisation through implementation and debugging;
• Carry out research and development and work on PoCs to trial and adopt new technologies;
• Collaborate with the other teams to address data sourcing and provision requirements;
• Coordinate with the Product & Technology teams to ensure all platforms collect and provide appropriate data;
• Liaise with the other Data & Analytics teams to ensure reporting and analytics needs can be addressed by the central data lake;
• Support the Data Quality and Security initiatives by building into the architecture the necessary data access, integrity, and accuracy controls.

Project detail

The Data Engineer will play a vital role as part of a cross-functional squad to develop data pipelines and the data lake to ingest, structure and expose data from a central location for integration, reports, analytics, and robotic process automation.