Data Engineer
Department: Digital Transformation
Job Purpose
- The Data Engineer is responsible for designing, building, and maintaining scalable data infrastructure and pipelines that support business intelligence, advanced analytics, and data science initiatives.
- This role ensures data is accessible, reliable, and structured for various business needs.
- The ideal candidate has strong engineering skills, a collaborative spirit, and experience working with large-scale data systems.
Scope of Work and Responsibilities
- Data Pipeline Development: Design, implement, and maintain efficient, scalable data pipelines to ingest, process, and transform data from various sources.
- Data Infrastructure: Build and manage robust data architectures using cloud platforms (e.g., AWS, GCP, Azure) and modern data technologies (e.g., Spark, Kafka, DataBricks, Snowflake).
- Database Management: Develop and optimize relational and non-relational databases, ensuring high availability and performance.
- Data Quality & Governance: Implement data validation, monitoring, and logging mechanisms to ensure data integrity and compliance with governance standards.
- Collaboration: Work closely with analysts, data scientists, and business stakeholders to understand data needs and deliver appropriate solutions.
- Automation & Tooling: Create reusable data tools and frameworks to improve pipeline development and deployment workflows.
- Performance Tuning: Monitor system performance and optimize processes for data processing efficiency.
- Documentation & Best Practices: Maintain clear documentation of data workflows and enforce best practices across teams.
- Agile Development: Participate in agile development cycles, contributing to continuous improvement in data engineering practices.
Technical Expertise
- Proficiency in Python, Java, or Rust for building data applications.
- Strong SQL skills and experience with relational databases (e.g., PostgreSQL, MySQL).
- Hands-on experience with data pipeline tools (e.g., Apache Airflow, dbt).
- Familiarity with distributed systems and big data technologies (e.g., Hadoop, Spark, Kafka).
- Experience with cloud-based data solutions (e.g., AWS Glue, Redshift, BigQuery, Azure Data Factory).
- Knowledge of CI/CD practices and version control tools like Git.
Qualifications
- Minimum of 7 years of experience in data engineering or a related backend/data infrastructure role.
- Bachelors degree in computer science, Engineering, Data Science, or a related technical field.
- Solid understanding of data warehousing concepts and ETL/ELT processes.
- Excellent problem-solving skills and attention to detail.
- Strong communication skills, with the ability to translate technical solutions to non-technical stakeholders.
- Comfortable working in a dynamic environment with agile teams and evolving requirements.
- Excellent communication skills in English both verbal and written
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