The Senior Data Analytics Engineer will develop strategies for and help design, build, and maintain the entire data layer for the analytics stack from top to bottom. This role involves close collaboration with various teams across data engineering, analytics, and visualization to deliver robust Business Intelligence solutions. The engineer will define and apply software engineering best practices such as version control, automated testing, documentation, code review, and continuous integration. Responsibilities include building data pipelines, creating data visualizations, and leading projects related to data ingestion, modeling, and warehouse design.
II. Roles & Responsibilities:
- Provide support and guidance to other Data Engineers.
- Manage the analytics data warehouse, implementing analytical database design principles and business process best practices.
- Design, develop,
and maintain scalable data pipelines using Apache Airflow.
- Integrate and manage data within Google BigQuery to meet analytics and reporting needs.
- Collaborate with cross-functional teams to understand data requirements and translate them into technical solutions.
- Implement ETL processes to ensure efficient data extraction, transformation, and loading from multiple sources.
- Optimize data workflows while ensuring data quality, consistency, and security.
- Monitor and troubleshoot performance and reliability of data pipelines.
- Stay current with trends and recent technologies in data engineering and cloud platforms.
- Identify, design, and implement internal process improvements such as automation, data delivery optimization, and infrastructure redesign for greater scalability.
- Support analytical requests cross-functionally for internal and external stakeholders.
III. Years of Experience:
- Minimum of 5 years experience work
📌 Data Engineer (Bengaluru)
🏢 DynPro
📍 Bengaluru
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