This role is for one of the Weekday's clients

Min Experience: 5+ years

Location: Bengaluru

JobType: full-time

We are seeking a highly skilled Senior Data Engineer with 5–8 years of experience in designing, developing, and maintaining modern data platforms that power business intelligence, analytics, and enterprise applications. The ideal candidate will have strong expertise in building scalable ETL pipelines, orchestrating workflows using Apache Airflow, and developing cloud-native data solutions on Snowflake.

You will work closely with data analysts, software engineers, business stakeholders, and product teams to deliver reliable, high-performance data infrastructure that supports critical business operations. Experience working with financial data, particularly within Corporate Finance or Commercial Banking, will be an added advantage.

Requirements

Key Responsibilities

• Design, develop, and optimize scalable ETL/ELT pipelines for ingesting, transforming, and loading structured and semi-structured data.
• Build and maintain reliable workflow orchestration using Apache Airflow, ensuring robust scheduling, monitoring, and failure recovery.
• Develop high-performance data warehouse solutions using Snowflake, leveraging its advanced features for storage optimization and query performance.
• Integrate data from multiple internal and external sources while ensuring consistency, quality, and integrity.
• Implement data validation, cleansing, and reconciliation processes across enterprise datasets.
• Collaborate with cross-functional teams to understand business requirements and translate them into scalable data engineering solutions.
• Optimize SQL queries, warehouse performance, and data models to improve reporting and analytical capabilities.
• Design and maintain metadata management, logging, monitoring, and alerting mechanisms for production data pipelines.
• Ensure adherence to security, governance, and compliance standards throughout the data lifecycle.
• Participate in code reviews, technical discussions, and architectural planning while mentoring junior data engineers.
• Support production deployments, troubleshoot pipeline failures, and continuously improve platform reliability and scalability.

Required Skills

Must-Have Skills

• Strong hands-on experience with Apache Airflow for workflow orchestration and pipeline automation.
• Expertise in Snowflake architecture, database design, performance tuning, and data warehousing best practices.
• Extensive experience building and maintaining ETL/ELT pipelines using modern data engineering practices.
• Advanced SQL programming and query optimization skills.
• Strong knowledge of Python for data engineering and automation.
• Experience working with cloud platforms such as AWS, Azure, or Google Cloud.
• Familiarity with CI/CD pipelines, Git version control, and DevOps practices.
• Understanding of data modeling, partitioning strategies, and data lifecycle management.
• Strong analytical, troubleshooting, and problem-solving abilities.

Good-to-Have Skills

• Domain knowledge in Corporate Finance, including financial reporting, accounting data, and enterprise finance systems.
• Experience working with Commercial Banking datasets, transaction processing, customer data, or regulatory reporting.
• Exposure to financial data governance, compliance standards, and risk management.
• Knowledge of streaming technologies, data lakes, or real-time data processing frameworks.
• Experience with BI and reporting platforms such as Power BI, Tableau, or Looker.

Qualifications

• Bachelor's or Master's degree in Computer Science, Information Technology, Engineering, or a related field.
• 5–8 years of professional experience in Data Engineering or related roles.
• Demonstrated experience delivering enterprise-scale data platforms in cloud environments.
• Excellent communication and collaboration skills with the ability to work across technical and business teams.