Senior GCP Data Engineer

Blackbuck-Insights; Bengaluru; Presencial; INR 300.000 - 450.000; Jornada completa

Descripción de la vacante

BBInsight in Bengaluru seeks a Senior Data Engineer to design, build, and optimize scalable data pipelines and cloud-based platforms supporting analytics and AI/ML initiatives. You will ensure reliable data ingestion, high-quality assets, and efficient processing while collaborating with architects, analysts, and stakeholders.

You will lead ETL/ELT development, implement data governance, observability, and automation, and guide junior engineers.

Formación

• Bachelor's degree in CS or a related field.
• 5+ years in Data Engineering or related disciplines.
• Strong SQL and programming in Python/Scala/Java.
• Experience with ETL/ELT pipelines and data warehousing.
• Cloud experience (Azure/AWS/GCP) and workflow orchestration tools (Airflow, ADF).
• Knowledge of data quality, governance, and monitoring.

Responsabilidades

• Design, build, and optimize scalable data pipelines.
• Develop ETL/ELT processes across enterprise platforms.
• Implement data integration for structured and unstructured data.
• Support Meridian data platform initiatives.
• Provide technical leadership and code reviews.
• Collaborate with architects, analysts, and stakeholders.

Conocimientos

SQL

Python

Java

Scala

Data engineering

Data governance

Airflow

CI/CD

Educación

Bachelor's degree in Computer Science, Engineering, Information Systems, or a related field

Herramientas

Databricks

Snowflake

Azure Synapse

Azure Data Factory

Kafka

Spark Streaming

Airflow

Descripción del empleo

BBI is a global data engineering consulting firm that empowers clients to effectively scale and modernize. We combine engineering fundamentals and innovative tools to execute business-critical, end-to-end projects on-time and on-budget. We offer expert services across Data Integration, Data Modernization, Data Migration, Data Architecture, Platform Support, and Application Services. Our goal is to provide business value in the most effective way for our clients so clients can focus on growth.

Job Description

The Senior Data Engineer is responsible for designing, building, and optimizing scalable data pipelines, data integration solutions, and cloud-based data platforms that support enterprise analytics, reporting, and AI/ML initiatives.

This role serves as a technical expert in data engineering, ensuring reliable data ingestion, high-quality data assets, and efficient data processing while collaborating closely with architects, analysts, and business stakeholders.

Key Responsibilities

• Design, develop, and maintain scalable and high-performance data pipelines.
  
• Build and optimize ETL/ELT processes to ingest, transform, and deliver data across enterprise platforms.
  
• Develop and maintain reusable data engineering frameworks and components.
  
• Implement data integration solutions for structured and unstructured data sources.
  
• Support modern cloud-based data platform initiatives.
  
• Data Ingestion & Pipeline Operations Develop and manage batch and real-time data ingestion pipelines.
  
• Monitor and optimize pipeline performance, reliability, and scalability.
  
• Troubleshoot data processing issues and implement corrective actions.
  
• Automate data workflows and orchestration processes.
  
• Ensure timely and accurate data delivery to downstream consumers.
  

Data Quality & Governance

• Implement data validation, reconciliation, and quality controls.
  
• Support data governance standards, metadata management, and data lineage initiatives.
  
• Identify and resolve data quality issues and causes.
  
• Contribute to data observability and monitoring solutions.
  
• Ensure compliance with organizational data management standards.
  
• Meridian Platform Support & Implementation Support the implementation and enhancement of Meridian data solutions.
  
• Develop integrations and data pipelines supporting Meridian initiatives.
  
• Collaborate with stakeholders to translate business requirements into technical solutions.
  
• Ensure successful deployment, testing, and operational support of Meridian-related capabilities.
  

Technical Leadership & Collaboration

• Provide technical guidance and mentorship to junior and mid-level engineers.
  
• Participate in architecture reviews, design sessions, and code reviews.
  
• Collaborate with data architects, product owners, analysts, and business stakeholders.
  
• Promote engineering best practices, automation, and continuous improvement.
  

Document technical designs, standards, and operational procedures.

Required Qualifications

• Bachelor's degree in Computer Science, Engineering, Information Systems, or a related field.
  
• 5+ years of experience in Data Engineering or related disciplines.
  
• Strong experience designing and developing enterprise data pipelines and integration solutions.
  
• Expertise in SQL and one or more programming languages such as Python, Scala, or Java.
  
• Experience with ETL/ELT frameworks, data warehousing, and data lake architectures.
  
• Experience with cloud platforms such as Azure, AWS, or Google Cloud. Knowledge of workflow orchestration tools such as Airflow, Azure Data Factory (ADF), or similar platforms.
  
• Strong understanding of data quality, data governance, and monitoring concepts.
  
• Experience troubleshooting and optimizing large-scale data processing solutions.
  

Requirements

• Experience with Meridian platform implementation or support.
  
• Experience with Data bricks, Snowflake, Azure Synapse, Microsoft Fabric, or similar modern data platforms.
  
• Knowledge of streaming technologies such as Kafka, Spark Streaming, or Event Hubs.
  
• Familiarity with DevOps practices, CI/CD pipelines, Infrastructure as Code (IaC), and automated testing.
  
• Experience supporting AI/ML data pipelines and feature engineering.
  
• Relevant cloud, data engineering, or platform certifications.
  
• Success Measures Reliable and scalable data pipelines with minimal operational issues.
  
• Improved data quality and reduced production defects. Timely delivery of data engineering solutions and enhancements.
  
• Successful implementation and support of Meridian data initiatives.
  
• Increased automation, operational efficiency, and platform stability.
  
• High-quality technical documentation and adherence to engineering standards.