Data Engineer

Role Overview

We seek a meticulous and analytical Data Engineer dedicated to designing, constructing, and maintaining dependable data systems and pipelines. The position involves converting raw data into precise, accessible datasets to enable business intelligence, analytics, reporting, and data-driven decisions.

Key Responsibilities

This role requires developing scalable data pipelines, integrating workflows, and processing solutions sourced from various data origins. Collaboration with data analysts, scientists, software developers, and business teams is essential to comprehend data needs and produce efficient, accurate, and well-organized data outputs. Responsibilities include monitoring data quality, enhancing data processing performance, diagnosing pipeline faults, and instituting improvements in data reliability and accessibility. The engineer will also contribute to data architecture, database design, ETL/ELT processes, governance, and documentation while fostering ongoing enhancements in the organization's data systems. Staying current on modern data technologies and promoting automation, scalability, security, and best practices in the data environment is also expected.

Qualifications and Skills

• A bachelor's degree in Computer Science, Data Engineering, IT, Mathematics, or a related field is required.
• Strong grasp of data engineering principles, ETL/ELT workflows, and database technologies.
• Proficient in SQL; experience with programming languages like Python, Java, or Scala.
• Knowledgeable in relational and non-relational databases, data modeling, and warehousing concepts.
• Experience or familiarity with cloud platforms such as AWS, Azure, or Google Cloud is an advantage.
• Preferred understanding of data processing and orchestration tools including Spark, Airflow, Kafka, or similar.
• Familiarity with Git and contemporary software development methodologies.
• Excellent analytical, troubleshooting, and problem-solving competencies.
• Strong awareness of data quality, security practices, governance, and comprehensive documentation.
• Detail-oriented with capability to manage extensive and complex datasets.
• Good communication skills aiding collaboration between technical and non-technical stakeholders.
• A proactive attitude with enthusiasm for data technology, automation, and continuous process improvement.
• Proficient in English; able to articulate technical concepts clearly.