Sr. Data Engineer

Overview

**Immediate Joiners Only**

The Data Engineer – GCP BigQuery Specialist will be responsible for designing and implementing efficient data pipelines that extract, transform, and load (ETL) data from various relational databases into Google Cloud BigQuery. The ideal candidate should have strong SQL optimization skills to ensure fast and efficient data processing and movement. They must be comfortable working in a multi-vendor, dynamic work environment and collaborating with cross-functional teams.

Key Responsibilities

1. Data Pipeline Development and Optimization

• Design and build scalable ETL/ELT data pipelines to transfer data from relational databases (SQL Server, PostgreSQL, MySQL, Oracle, etc.) to GCP BigQuery.
• Implement best practices for efficient data ingestion using tools such as Apache Airflow, Dataflow, Cloud Composer, and BigQuery Data Transfer Service.
• Optimize SQL queries for high-performance data movement and processing in BigQuery.

2. Performance Tuning and Optimization

• Write and optimize complex SQL queries to ensure fast and cost-efficient data transformations.
• Monitor and fine-tune BigQuery performance using clustering, partitioning, and query execution plans.
• Implement best practices for cost optimization on BigQuery, reducing query costs and improving efficiency.

3. Data Architecture and Schema Design

• Design and implement schema models in BigQuery, including denormalization techniques, partitioning, and clustering strategies.
• Collaborate with Data Architects to ensure scalability, reliability, and security of data architectures.
• Work with business teams to define data models that align with analytics and reporting needs.

4. Data Integration and Transformation

• Develop real-time and batch data processing solutions using Cloud Dataflow, Pub/Sub, and Cloud Functions.
• Implement data cleansing, enrichment, and transformation using SQL, Python, or Apache Beam.
• Integrate data from multiple sources (structured, semi-structured, unstructured) into BigQuery.

5. Cloud Infrastructure & Security

• Manage GCP IAM roles and permissions to ensure secure access to data.
• Implement data governance and compliance policies for handling sensitive data in BigQuery.
• Utilize Cloud Logging and Monitoring (Stackdriver, Cloud Logging, Cloud Monitoring) for troubleshooting and performance monitoring.

6. Collaboration in a Multi-Vendor, Dynamic Work Environment

• Work in a fast-paced environment with multiple vendors, cloud service providers, and technology partners.
• Collaborate with data analysts, data scientists, and business intelligence teams to understand requirements and provide efficient data solutions.
• Coordinate with cross-functional teams across different geographical locations and time zones.

Job Type: Full-time

Pay: ₹1,000,000.00 - ₹4,500,000.00 per year

Schedule:

• Day shift
• Monday to Friday

Experience:

• total: 5 years (Required)
• GCP: 5 years (Required)
• Python: 5 years (Required)
• SQL: 5 years (Required)

Work Location: Remote