Weekday AI

Data Engineer

Weekday AI · Chennai, Tamil Nadu, India · ₹600K–₹1M/yr

Technology, Information and Internet · 11-50 employees

5 h ago
Senior (5-10 yrs) Full-time India
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About the role

Design, develop, and maintain cloud-native data pipelines for ingesting and transforming structured and unstructured data. Collaborate with cross-functional teams to support analytics, machine learning, and AI initiatives while ensuring data quality and governance.

What they look for

Google Cloud Platform BigQuery Data Engineering SQL Python dbt Apache Airflow Cloud Composer PostgreSQL Terraform CI/CD Data Pipelines ETL/ELT Infrastructure as Code DevOps Data Governance

Requirements

Requires 5+ years of professional experience in data engineering and cloud-native platform development. Strong hands-on expertise with Google Cloud Platform, BigQuery, dbt, SQL, Python, and infrastructure automation tools is essential.

Full description

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.

Key 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.

What Makes You a Great Fit• 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.