
Lead Data Pipeline Developer
3 days ago
Our organization is seeking a skilled and motivated data engineer to design, develop, and maintain scalable data pipelines that process and transform large volumes of structured and unstructured data. The ideal candidate will have a strong background in data engineering, cloud technologies, and data architecture, and will collaborate closely with data scientists, analysts, and business teams to deliver high-quality data solutions.
- Design and implement scalable data pipelines for processing structured and unstructured data, utilizing tools such as Apache Spark and Cloud Storage.
- Develop and maintain ETL/ELT workflows for data ingestion from diverse sources including APIs, databases, files, and cloud platforms.
- Ensure data quality, integrity, and governance across all data pipelines by implementing robust data validation and error handling mechanisms.
- Collaborate with cross-functional teams to understand and fulfill data requirements, fostering open communication and transparency throughout the process.
- Optimize data workflows for performance and reliability, leveraging expertise in data optimization techniques and emerging technologies.
Key Responsibilities:
Programming & Data Engineering:
- Proficiency in Python, PySpark, and SQL programming languages.
- Strong understanding of CI/CD practices and version control systems like Git.
Streaming & Orchestration:
- Experience with Kafka and GCP Composer/Apache Airflow.
Cloud Tools:
- Proficient in Google Cloud Platform (Dataproc, BigQuery, Looker) with experience in designing and deploying scalable data architectures.
Data Architecture:
- Knowledge of data warehousing and data modeling concepts.
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