Senior Data Engineer

This role is for one of the Weekday's clients

Min Experience: 8 years

Location: Bangalore

JobType: full-time

We are seeking an experienced and highly skilled Senior Data Engineer to design, build, and optimize scalable data platforms that power analytics, reporting, and data-driven decision-making across the organization. The ideal candidate will have deep expertise in Snowflake, AWS, data lake architectures, Python, PySpark, SQL, and Oracle Database, along with a strong understanding of modern data engineering best practices. This role requires hands-on technical leadership, ownership of complex data pipelines, and close collaboration with analytics, product, and business teams.

Requirements

Key Responsibilities

• Design, develop, and maintain scalable and high-performance data pipelines using Python, PySpark, and SQL to support batch and near real-time data processing.
• Build and manage enterprise-grade data lake architectures on AWS, ensuring reliability, scalability, and cost efficiency.
• Implement and optimize Snowflake data warehouse solutions, including schema design, data modeling, performance tuning, and query optimization.
• Integrate data from multiple structured and unstructured sources, including Oracle Database, into centralized data platforms.
• Develop robust ETL/ELT frameworks to ensure high data quality, consistency, and availability across systems.
• Collaborate with data analysts, data scientists, and business stakeholders to understand data requirements and deliver optimized data solutions.
• Apply best practices for data security, governance, and compliance, including access controls, encryption, and auditing.
• Monitor, troubleshoot, and optimize data workflows to ensure system reliability and performance at scale.
• Provide technical mentorship and guidance to junior data engineers and contribute to architectural and design decisions.
• Participate in code reviews, documentation, and continuous improvement of data engineering standards and processes.

Required Skills & Qualifications

• 8–12 years of experience in data engineering, building large-scale data platforms and pipelines.
• Strong hands-on experience with Snowflake, including data modeling, performance optimization, and cost management.
• Proven expertise in designing and implementing data lakes on AWS (e.g., S3, Glue, Lambda, EMR, Redshift, or related services).
• Advanced programming skills in Python and PySpark for distributed data processing.
• Excellent command of SQL for complex data transformations and analytics use cases.
• Solid experience working with Oracle Database, including data extraction, integration, and performance considerations.
• Strong understanding of data warehousing concepts, dimensional modeling, and big data processing frameworks.
• Experience with CI/CD pipelines, version control, and automated testing for data workflows.
• Strong problem-solving skills and the ability to work independently in a fast-paced environment.

Nice to Have

• Experience with real-time data processing or streaming technologies.
• Exposure to data governance, metadata management, or data catalog tools.
• Prior experience in mentoring or leading small engineering teams.