BigQuery Data Engineer

Title: Data Engineer

Location: Pune, India

About DataNimbus:

At DataNimbus, we are on a mission to redefine how organizations leverage Data and AI to drive growth, innovation, and efficiency. Our pioneering products, such as DataNimbus Designer (a cloud-native ETL designer), datanimbus.io (a comprehensive data and integration platform), FinHub.ai (payment modernization platform) empower businesses to simplify complex workflows, adopt cutting-edge technology, and achieve sustainable scalability.

With headquarters in the U.S. and offices in India and Canada, DataNimbus operates globally, fostering a culture of responsible innovation, adaptability, and customer-centricity. We pride ourselves on being a trusted partner for customers navigating the complexities of Data+AI and payment modernization.

Why Join DataNimbus?

At DataNimbus, we believe in shaping a sustainable, AI-driven future while offering an environment that prioritizes learning, innovation, and growth. Our core values—Customer-Centricity, Simplicity, Curiosity, Responsibility, and Adaptability—are the foundation of our workplace, ensuring every team member can make a meaningful impact. Joining DataNimbus means being part of a dynamic team where you can:

• Work with cutting-edge technologies and revolutionize workflows in Data+AI solutions.
• Contribute to solutions that are trusted by global businesses for their scalability, security, and efficiency.
• Grow personally and professionally in a culture that values curiosity and continuous learning.
• If you're passionate about innovation, ready to solve complex challenges with simplicity, and eager to make a difference, DataNimbus is the place for you.

Qualifications:

• 6+ years of experience in Data Engineering, with at least 3+ years working on BigQuery in a production environment.
• Strong SQL expertise, including query optimization and advanced SQL features.
• Proficiency in at least one programming language (Python, Java, or Scala).
• Experience with cloud data ecosystem (Google Cloud Platform preferred).
• Strong understanding of data modeling, star/snowflake schemas, and OLAP concepts.
• Hands-on experience with ETL/ELT frameworks and workflow orchestration tools (Airflow, Cloud Composer, dbt).
• Knowledge of data governance, lineage, and security practices.
• Familiarity with streaming/batch data ingestion (Pub/Sub, Kafka, or equivalent).
• Exposure to machine learning workflows in BigQuery ML.
• Experience with BI/visualization tools such as Looker, Tableau, or Power BI.

Key Responsibilities:

• Design, develop, and maintain a highly scalable data warehouse solution in BigQuery.
• Architect data models, schemas, and partitioning strategies for efficient query performance.
• Build and maintain ETL/ELT pipelines using tools such as Dataflow, Dataproc, Cloud Composer (Airflow), or dbt.
• Optimize query performance and manage cost-efficient BigQuery usage.
• Implement data governance, security, and compliance best practices (IAM, data masking, audit logging).
• Collaborate with data analysts, data scientists, and business stakeholders to deliver reliable, high-quality datasets.
• Ensure data quality and consistency through monitoring, validation, and testing.
• Mentor junior engineers and contribute to best practices, coding standards, and documentation.