Job Summary We are looking for a skilled Data Engineer / Senior Data Engineer with 4–6 years of overall experience and strong hands-on expertise in Python, SQL, and Google Cloud Platform (GCP). The candidate will be responsible for designing, developing, and maintaining scalable, distributed, and fault-tolerant data pipelines and data applications. The ideal candidate should have practical experience working with BigQuery, Dataflow, Google Cloud Storage (GCS), PostgreSQL, and cloud-based or traditional data warehouse environments. Experience with Apache Spark, Kafka, Hadoop, Cloud Composer, Pub/Sub, Cloud Functions, and Cloud SQL will be an added advantage. Job Responsibilities
• Design, develop, and maintain scalable and fault-tolerant data pipelines from scratch.
• Build, optimize, and maintain data solutions using Python and SQL.
• Develop data pipelines and applications using GCP services such as BigQuery, Dataflow, and GCS.
• Work with relational and non-relational databases to support data integration and analytics requirements.
• Develop and maintain data applications across cloud-based and traditional data warehouse environments.
• Ensure data pipelines are reliable, scalable, highly available, and performant.
• Troubleshoot data pipeline and production issues and implement effective solutions.
• Collaborate with engineering, analytics, and business teams to understand requirements and deliver data solutions.




• Work with big data technologies such as Apache Spark, Hadoop, and Kafka, wherever required.
• Identify and adopt new tools and technologies to improve data engineering processes.
• Provide technical guidance and support to current team members.
• Contribute to code reviews, documentation, testing, and engineering best practices. Required Skills
• 4–8 years of experience in Data Engineering.
• 3+ years of hands-on experience in Python and SQL.
• Strong experience with Google Cloud Platform (GCP), particularly:
• BigQuery
• Dataflow
• Google Cloud Storage (GCS)
• Hands-on experience with PostgreSQL and relational databases.
• Knowledge of NoSQL databases and data integration techniques.
• Minimum 2 years of experience in data pipeline development.
• Strong understanding of ETL/ELT processes and distributed systems.
• Experience working with cloud-based and traditional data warehouses.
• Exposure to Apache Spark, Kafka, and Hadoop is preferred.
• Strong problem-solving, analytical, and communication skills.
• Ability to work independently and adapt to dynamic environments with evolving requirements. We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, sex, gender, gender expression, sexual orientation, age, marital status, veteran status, or disability status.

📌 Senior Analyst (Chennai)
🏢 LATENTVIEW ANALYTICS
📍 Chennai