Role & responsibilities

1. Lead the architecture, design, and implementation of scalable data lake and pipeline solutions on Google Cloud Platform.
2. Build efficient, reusable, and scalable data flows using Dataflow, Pub/Sub, and BigQuery.
3. Design and optimize cloud-native data storage and processing frameworks.
4. Build and manage real-time dashboards and data visualizations to support decision-making across the organization.
5. Manage and monitor real-time and batch data pipeline health, accuracy, and reliability.
6. Work closely with data analysts, scientists, and product teams to deliver clean and reliable datasets.
7. Ensure best practices for data security, governance, monitoring, and cost optimization.
8. Drive data quality management initiatives including validation, lineage, and version control.
9.



Mentor junior engineers and guide best practices in Python and SQL-based data engineering.

Qualification Required

1. 8+ years of data engineering experience with strong GCP expertise.
2. Proven experience in building and maintaining data lakes and real-time data pipelines.
3. Deep understanding of distributed data processing using Dataflow, Dataproc, and BigQuery.
4. Robust coding skills in Python and SQL.
5. Hands-on experience with real-time dashboarding tools (e.g., Looker, Data Studio, Power BI, etc.).
6. Solid knowledge of cloud storage, data modeling, and performance tuning.
7. Experience in monitoring, logging, and alerting for data systems.

Excellent problem-solving, leadership, and cross-functional collaboration skills

📌 Lead Data Engineer (Mumbai)
🏢 AstaGuru
📍 Mumbai