Job Summary

- We are seeking a skilled Senior Analyst - Data Engineer with strong hands-on experience in designing, building, and maintaining scalable data pipelines and cloud-based data solutions. The ideal candidate will have expertise in Python, SQL, and Google Cloud Platform (GCP) services, with the ability to develop reliable, high-performance, and fault-tolerant data processing solutions.
- The role requires hands-on experience with BigQuery, Dataflow, Google Cloud Storage (GCS), Dataproc, Cloud SQL, Cloud Functions, Pub/Sub, and Cloud Composer, along with a strong understanding of ETL/ELT, distributed data processing, and modern data engineering practices.

Key Responsibilities

- Design, develop, and maintain scalable end-to-end data pipelines to extract, transform, and load data from diverse sources.
- Build reliable, scalable, and performance-oriented ETL/ELT pipelines using GCP data services and modern data engineering technologies.
- Develop and optimize complex SQL queries for data extraction, transformation, analysis, and reporting.
- Build and manage large-scale data processing solutions using BigQuery, Dataflow, Dataproc, and Google Cloud Storage (GCS).
- Develop distributed and fault-tolerant data pipelines capable of handling large volumes of structured and unstructured data.
- Work with a broad range of relational and non-relational databases to support diverse data processing requirements.
- Utilize Cloud SQL, Cloud Functions, Pub/Sub, and Cloud Composer for data storage, event-driven processing, automation, and workflow orchestration.
- Develop and maintain batch and real-time data processing solutions using technologies such as Apache Spark,



Hadoop, and Kafka.
- Collaborate with data analysts, data scientists, and other cross-functional teams to understand data requirements and deliver scalable solutions.
- Support the integration of new cloud technologies and tools into the existing data ecosystem.
- Monitor and optimize data pipelines for performance, scalability, reliability, and fault tolerance.
- Document data pipelines, technical processes, architecture, and best practices to support knowledge sharing and operational efficiency.
- Troubleshoot and resolve data pipeline, infrastructure, and performance-related issues.
- Continuously explore and adopt new tools, technologies, and best practices in cloud and data engineering.

Required Skills:

- 4 to 6 years of professional experience in Data Engineering, Data Platform Engineering, or related roles.
- Strong hands-on experience with Python and SQL for data processing and transformation.
- 3+ years of hands-on experience with Google Cloud Platform (GCP) data services.
- Strong experience with BigQuery, Dataflow, Google Cloud Storage (GCS), and Dataproc.
- Experience designing and building scalable ETL/ELT and end-to-end data pipelines from scratch.
- Strong understanding of distributed and fault-tolerant data processing architectures.




- Hands-on experience with Cloud SQL, Cloud Functions, Pub/Sub, and Cloud Composer.
- Experience working with both relational and non-relational databases.
- Familiarity with cloud-based and traditional Data Warehouse architectures.
- Knowledge of big data technologies such as Apache Spark, Hadoop, and Kafka.
- Understanding of batch and real-time/streaming data processing.
- Familiarity with data engineering applications involving big data and machine learning platforms is an added advantage.
- Ability to work effectively in a dynamic environment where requirements and problems may not always be well-defined.
- Inquisitive mindset with a proactive approach to learning new tools, technologies, and data engineering practices.

Why Join Us?

- Opportunity to work on modern, large-scale data engineering and cloud transformation initiatives.
- Hands-on exposure to a wide range of GCP data services, including BigQuery, Dataflow, Dataproc, GCS, Pub/Sub, and Cloud Composer.
- Chance to design and build scalable, distributed, and fault-tolerant data pipelines from the ground up.
- Exposure to modern data warehousing, big data, streaming, and cloud-native architectures.
- Collaborative environment with opportunities to work closely with data engineers, analysts, data scientists, architects, and business teams.
- Opportunity to continuously learn and work with emerging technologies in cloud, data engineering, big data, and analytics.
- Culture that encourages innovation, continuous learning, technical excellence, collaboration, and ownership.

📌 Senior Analyst - Data Engineering (Chennai)
🏢 Latentview
📍 Chennai