Design, build, and optimize cloud-native data pipelines and platforms on GCP. Develop ETL/ELT workflows with SQL and Python, implement transformations with dbt, orchestrate jobs with Airflow, provision infrastructure via Terraform, maintain CI/CD, ensure data quality/governance, and support analytics, ML, and production stability.
𝗧𝗵𝗶𝘀 𝗿𝗼𝗹𝗲 𝗶𝘀 𝗳𝗼𝗿 𝗼𝗻𝗲 𝗼𝗳 𝘁𝗵𝗲 𝗪𝗲𝗲𝗸𝗱𝗮𝘆'𝘀 𝗰𝗹𝗶𝗲𝗻𝘁𝘀
𝗦𝗮𝗹𝗮𝗿𝘆 𝗿𝗮𝗻𝗴𝗲: 𝗥𝘀 𝟲𝟬𝟬𝟬𝟬𝟬 - 𝗥𝘀 𝟭𝟮𝟬𝟬𝟬𝟬𝟬 (𝗶𝗲 𝗜𝗡𝗥 𝟲-𝟭𝟮 𝗟𝗣𝗔)
Experience: 5+ yrs
Location: Chennai, Tamil Nadu, India
Job Type: Full-time
We are seeking a highly skilled Data Engineer to design, develop, and optimize cloud-native data platforms that enable scalable analytics, business intelligence, and data-driven decision-making. This role is ideal for professionals with strong expertise in modern data engineering, Google Cloud Platform (GCP), and data transformation frameworks who are passionate about building reliable, high-performance data solutions.
As a Data Engineer, you will work closely with data architects, analytics teams, software engineers, and business stakeholders to develop robust data pipelines, manage cloud-based data infrastructure, and ensure high standards of data quality, governance, and performance. You will play a key role in building scalable batch and streaming data solutions while supporting advanced analytics, AI, and customer-facing data applications.
RequirementsKey Responsibilities
- Design, develop, and maintain cloud-native data pipelines for ingesting, transforming, and delivering structured and unstructured data.
- Build scalable data solutions using Google Cloud Platform (GCP) services, including BigQuery and related cloud technologies.
- Develop and maintain data transformation frameworks using dbt to support analytics and reporting requirements.
- Create efficient ETL/ELT workflows using SQL, Python, and cloud-native data engineering best practices.
- Orchestrate and automate data workflows using Apache Airflow or Cloud Composer.
- Design and optimize relational database solutions, including PostgreSQL and other enterprise database platforms.
- Implement Infrastructure as Code (IaC) using Terraform to provision and manage cloud infrastructure.
- Build and maintain CI/CD pipelines using GitHub Actions, GitLab CI, Jenkins, or similar DevOps tools.
- Optimize data processing pipelines for scalability, reliability, performance, and cloud cost efficiency.
- Collaborate with cross-functional teams to support analytics, machine learning, AI, and customer-facing data initiatives.
- Implement data quality, governance, metadata, and lineage practices to improve trust and consistency across enterprise data assets.
- Monitor production environments, troubleshoot pipeline failures, and continuously improve platform performance and operational stability.
- 5+ years of professional experience in Data Engineering and cloud-native data platform development.
- Strong hands-on expertise with Google Cloud Platform (GCP), including BigQuery and modern cloud data services.
- Proven experience building scalable data transformation frameworks using dbt.
- Advanced proficiency in SQL and Python for data engineering, automation, and pipeline development.
- Experience working with relational databases such as PostgreSQL and enterprise data management solutions.
- Hands-on experience orchestrating workflows using Apache Airflow or Cloud Composer.
- Strong understanding of Infrastructure as Code using Terraform and modern DevOps practices.
- Experience developing CI/CD pipelines using GitHub Actions, GitLab CI, Jenkins, or similar automation tools.
- Knowledge of streaming and batch processing architectures, cloud infrastructure, and distributed data systems.
- Familiarity with services such as Pub/Sub, Dataflow, Datastream, Cloud Storage, Cloud Functions, Cloud Run, Kubernetes, Docker, or similar cloud technologies is an advantage.
- Strong analytical, troubleshooting, and communication skills with the ability to build scalable, secure, and cost-efficient enterprise data solutions.
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