Job description
We are seeking a highly skilled and experiencedSenior Data Engineerto design, develop, and optimize scalable data pipelines, ensuring the availability, performance, and reliability of our data systems. The ideal candidate will have a deep understanding of data architecture, ETL processes, and cloud technologies, with the ability to lead complex projects and mentor junior team members.
Key Responsibilities
1. Data Infrastructure Design and Development
- Design and implement robust, scalable, and efficient data pipelines to support business analytics and decision-making.
- Develop, test, and maintain ETL/ELT workflows using modern tools and technologies.
- Ensure data quality, consistency, and reliability across all pipelines and systems.
2. Data Architecture and Modelling
- Build and optimize data architectures for large-scale, distributed systems.
- Develop data models and schemas to support analytical and operational reporting.
- Design strategies for data warehousing and data lake integration.
3. Technology and Tools Management
- Leverage cloud platforms (e.g., AWS, Azure, GCP) to build and manage scalable solutions.
- Work with big data technologies such as Hadoop, Spark, Kafka, or similar tools.
- Manage relational and NoSQL databases (e.g., PostgreSQL, MongoDB, Cassandra).
4. Collaboration and Mentorship
- Collaborate with data scientists, analysts, and software engineers to meet organizational goals.
- Mentor and guide junior engineers, promoting best practices in coding, architecture, and data management.
- Partner with stakeholders to translate business requirements into technical solutions.
5. Performance Optimization and Security
- Monitor and improve data pipeline performance, addressing bottlenecks and inefficiencies.
- Implement security best practices to ensure the safety and privacy of data.
- Automate routine processes to reduce manual intervention and operational overhead.
Required Skills and Qualifications
- Education: Bachelors or Master's degree in Computer Science, Data Engineering, or a related field.
- Experience:
- 3-8 years of experience in data engineering or related roles.
- Proven expertise in designing and building large-scale data pipelines and architectures.
- Technical Skills:
- Proficiency in programming languages like Python, Java, or Scala.
- Advanced SQL skills for complex queries and performance tuning.
- Hands-on experience with cloud platforms (AWS, Azure, GCP).
- Experience with big data tools (e.g., Spark, Hadoop, Kafka).
- Knowledge of containerization (e.g., Docker) and orchestration tools (e.g., Kubernetes, Airflow).
- Soft Skills:
- Strong problem-solving abilities and attention to detail.
- Excellent communication and collaboration skills.
- Ability to lead projects and work independently in a fast-paced environment.
Preferred Qualifications
- Certification in cloud platforms like AWS Certified Data Analytics Specialty, Google Professional Data Engineer, or Azure Data Engineer Associate.
- Experience with streaming data pipelines and real-time processing.
- Familiarity with machine learning workflows and tools.
- Knowledge of data governance and compliance standards.
