Role Overview
As a Senior Data Pipeline Engineer, you will play a crucial role in designing and implementing robust data pipelines that drive critical business decisions. Your expertise will facilitate the seamless integration of diverse data sources into data warehouses, ensuring that data is reliable and accessible. Collaborating with cross-functional teams, you will leverage your technical skills to optimize data processing and contribute to advanced analytics solutions.
Key Responsibilities:
- Design and implement scalable data pipelines to support various analytical needs.
- Optimize and monitor ETL processes for efficiency and reliability.
- Collaborate with data scientists to ensure data readiness for machine learning models.
- Develop strong data quality checks and validation processes to enhance data integrity.
- Work closely with the DevOps team to ensure seamless deployments and integrations.
- Troubleshoot and resolve issues related to data flow and processing.
- Document data pipeline architectures and processes for future reference.
- Conduct performance tuning and optimization of data storage and retrieval systems.
- Mentor junior team members on best practices for data pipeline development.
Required Skills:
- Python programming for data manipulation and automation.
- Strong proficiency in SQL for database querying and management.
- Experience with cloud platforms such as AWS or GCP.
- Familiarity with big data technologies like Hadoop or Spark.
- Knowledge of ETL tools and frameworks.
- Proficient in using version control systems like Git.
- Ability to implement data security standards and practices.
- Strong problem-solving and analytical skills.
- Excellent communication skills for effective collaboration.
Preferred Skills:
- Experience with orchestration tools such as Apache Airflow.
- Familiarity with NoSQL databases like MongoDB or Cassandra.
- Knowledge of data visualization tools like Tableau or Power BI.
