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Salary
≈ $20k – $40k per year (Estimated)
Location
In office (Pune, Chennai, Bengaluru)
Experience
6+ years exp

First seen by Alion on Sep 29, 2026.

Overview
Company
Impact
Profile match
Rarrtech helps MSMEs build scalable systems using Cloud ERP, AI, and IoT solutions to reduce operational complexity and improve efficiency.

We are looking for an experienced GCP Data Engineer with strong hands-on expertise in designing and developing cloud-based data pipelines and a solid understanding of BI and reporting platforms. The role will involve building scalable data solutions on Google Cloud Platform, developing ETL/ELT pipelines, optimizing data processing, and supporting business analytics through Power BI, Qlik Sense, or Tableau.

The ideal candidate should have strong experience with BigQuery, Dataflow, Dataproc, Cloud Storage, Cloud Composer, SQL, Python, data warehousing, and dimensional modelling, along with hands-on experience in at least one BI visualization platform.

Key Responsibilities :

- Design, develop, and maintain scalable data pipelines and data-processing solutions on Google Cloud Platform (GCP).

- Work with GCP services including BigQuery, Cloud Storage, Dataflow, Dataproc, and Cloud Composer.

- Develop and maintain robust ETL/ELT pipelines using SQL, Python, and cloud-native data engineering tools.

- Perform data extraction, transformation, integration, validation, and optimization across multiple data sources.

- Design and implement data models supporting operational reporting, analytics, and business intelligence requirements.

- Work with data warehouses, dimensional models, fact and dimension structures, and analytical data platforms.

- Optimize BigQuery queries, data pipelines, and processing workloads for performance, scalability, reliability, and cost efficiency.

- Develop and maintain dashboards, reports, and analytical solutions using Power BI, Qlik Sense, or Tableau.

- Collaborate with business, BI, analytics, and data teams to understand reporting requirements and translate them into effective data solutions.

- Ensure data pipelines meet defined standards for data quality, accuracy, availability, and reliability.

- Implement appropriate monitoring, logging, error handling, and troubleshooting mechanisms for data workflows.

- Investigate and resolve data pipeline failures, data-quality issues, and performance bottlenecks.

- Support data integration across cloud, enterprise applications, and downstream reporting platforms.

- Participate in code reviews, technical design discussions, testing, deployment, and release activities.

- Maintain technical documentation covering data pipelines, data models, integrations, and operational procedures.

- Contribute to automation, standardization, and continuous improvement of data engineering and BI processes.

Required Skills & Experience :

- 6 - 11 years of experience in Data Engineering, BI Engineering, or a related data technology role.

- Strong hands-on experience in GCP Data Engineering.

- Strong expertise with BigQuery and good knowledge of Cloud Storage, Dataflow, Dataproc, and Cloud Composer.

- Strong proficiency in SQL and Python.

- Hands-on experience developing ETL/ELT pipelines and data integration solutions.

- Good understanding of data warehousing, dimensional modelling, data transformation, and analytical data structures.

- Hands-on experience with at least one BI platform: Power BI, Qlik Sense, or Tableau.

- Experience developing dashboards, reports, data visualizations, and analytical solutions.

- Strong understanding of data quality, data validation, pipeline monitoring, and troubleshooting.

- Good understanding of cloud-based data architecture and scalable data-processing patterns.

- Experience with Git, CI/CD, testing, and deployment practices.

- Strong analytical, problem-solving, and communication skills.

- Ability to work effectively with business, analytics, BI, and technical stakeholders.

Skills

Data Engineering, Google Cloud Platform, Data Pipeline, BigQuery, SQL, Python, Data Warehousing, Tableau, Business Intelligence

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