Senior Data engineer

Weekday AI


Date: 2 weeks ago
City: Pune, Maharashtra
Contract type: Full time

This role is for one of the Weekday's clients

Salary range: Rs 1500000 - Rs 2000000 (ie INR 15-20 LPA)

Experience: 5+ yrs

Location: Bangalore, PUNE, Hyderabad

Job Type: full-time

We are seeking an experienced Data Engineer with 5–10 years of expertise in building and managing modern data platforms. The ideal candidate will have strong hands-on experience with Snowflake, DBT, Airflow, Python, and IICS (Informatica Intelligent Cloud Services), along with a solid understanding of cloud-based data architectures and data integration frameworks.

In this role, you will be responsible for designing, developing, and optimizing scalable data pipelines and analytical data models that support enterprise reporting, business intelligence, and advanced analytics initiatives. You will collaborate with cross-functional teams to deliver high-quality data solutions, ensure data reliability, and drive best practices in data engineering, automation, and performance optimization.

Requirements

Key Responsibilities

  • Design, develop, and maintain scalable ETL/ELT pipelines for processing and integrating data from multiple sources.
  • Build and manage data transformation workflows using DBT, ensuring modular, reusable, and well-documented SQL development practices.
  • Develop and optimize Snowflake data warehouse solutions, including data modeling, query tuning, and warehouse performance optimization.
  • Create and maintain workflow orchestration processes using Airflow, including DAG development, scheduling, monitoring, and troubleshooting.
  • Develop Python-based solutions for data processing, automation, scripting, and integration requirements.
  • Design and implement ETL/ELT workflows using Informatica Intelligent Cloud Services (IICS).
  • Develop and maintain robust data models that support reporting, analytics, and business intelligence use cases.
  • Monitor data pipelines and workflows to ensure reliability, scalability, and high availability.
  • Collaborate with business stakeholders, analysts, and engineering teams to understand data requirements and translate them into technical solutions.
  • Implement data quality checks, validation frameworks, and monitoring processes to maintain data integrity.
  • Optimize database and warehouse performance through effective partitioning, clustering, workload management, and query optimization techniques.
  • Participate in code reviews, technical design discussions, and continuous improvement initiatives.
  • Support CI/CD implementation, deployment automation, and version control best practices using Git.
  • Ensure adherence to data governance, security, and compliance standards across all data engineering processes.

What Makes You a Great Fit

  • 5–10 years of professional experience in Data Engineering, Data Warehousing, or related fields.
  • Strong expertise in Snowflake, including data modeling, performance tuning, warehouse optimization, and cost management.
  • Hands-on experience with DBT for data transformation, modular SQL development, and analytics engineering practices.
  • Proven experience with Airflow for workflow orchestration, DAG development, scheduling, and monitoring.
  • Advanced proficiency in Python for data engineering, automation, scripting, and data processing tasks.
  • Experience working with Informatica Intelligent Cloud Services (IICS) for ETL/ELT development and integration.
  • Strong command of SQL and relational database concepts, including complex query development and optimization.
  • Experience working with cloud platforms such as AWS, Azure, or GCP.
  • Knowledge of CI/CD pipelines, Git, and modern software development practices.
  • Strong analytical, troubleshooting, and problem-solving capabilities.
  • Excellent communication and stakeholder management skills, with the ability to work effectively in collaborative, cross-functional environments.
  • Passion for building scalable, high-performance data solutions and driving data-driven decision-making across the organization.

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