Role Overview
As a Senior Data Pipeline Engineer, you will be responsible for designing, building, and optimizing data pipelines that ensure reliable data flows from various sources to target systems. The role demands a strong background in data engineering and a passion for solving complex data challenges. You will work closely with data scientists and analysts to provide them with high-quality, structured data for their initiatives. Your expertise will shape our data strategy and drive significant improvements in our data capabilities.
Key Responsibilities:
- Design and implement data pipelines that facilitate efficient data flow and processing.
- Collaborate with data scientists to understand their data needs and ensure pipeline alignment.
- Optimize existing ETL processes for improved performance and reliability.
- Develop and maintain robust documentation for all data processes and workflows.
- Monitor and troubleshoot data issues to ensure seamless operations on the data platform.
- Identify and implement best practices for data pipeline architecture and governance.
- Coordinate with cross-functional teams to integrate systems and tools effectively.
- Stay updated on emerging technologies and methodologies in data engineering.
Required Skills:
- Strong experience in Python and/or Java for data processing.
- Proficiency in SQL for data manipulation and querying.
- Solid understanding of ETL tools like Apache Airflow or Talend.
- Experience with cloud platforms such as AWS, Azure, or Google Cloud.
- Familiarity with big data technologies like Hadoop or Spark.
- Knowledge of data modeling and database design principles.
- Ability to work with APIs for data integration.
- Strong analytical and problem-solving skills.
Preferred Skills:
- Experience with NoSQL databases like MongoDB or Cassandra.
- Familiarity with data visualization tools such as Tableau or Power BI.
- Experience in machine learning concepts and practices.
