Staff Data Engineer

Overview

Design, implement, and improve secure, scalable, high-quality data applications and systems as a Staff Data Engineer. Work hands-on with code, data, modern tools, cloud services, automation frameworks, and AI-assisted development while collaborating with cross-functional teams to deliver technology solutions in the fintech sector.

What you'll do

• Understand data ecosystems, security, privacy, and retention requirements to support business and product features.
• Participate in stakeholder meetings to identify and clarify requirements and determine business needs.
• Translate functional requirements into architecture designs for one or more components using existing architecture design patterns, and communicate these to Data Engineers.
• Implement extensible, maintainable, and reusable code using appropriate coding patterns, guidelines, and best practices.
• Participate in code reviews to ensure standards are followed.
• Provide end-to-end ownership of data products or data pipelines, including mitigation of technical debt and documentation of errors or unexpected bugs.
• Identify and conduct required testing for moderately complex use cases, including unit testing, coding standards, and security scans.
• Build tools and standard automation processes to transform, manage, access, deploy, and monitor data processes in batches and in real time.
• Write queries to extract and compile raw data across end-to-end pipelines, and implement orchestration techniques to automate data extraction logic.
• Ensure adherence to data management principles, governance, and tools to maintain data quality across multiple features.
• Develop and update troubleshooting guidance and procedures for reviewing, addressing, and fixing advanced problems flagged by testing.
• Manage software upgrades and server patches for security remediation where applicable.

What you'll need

• 6+ years of relevant work experience with a Bachelor's Degree, or at least 2 years of work experience with an Advanced degree (e.g. Masters, MBA, JD, MD), or 0 years of work experience with a PhD, or 8+ years of relevant work experience.
• Experience in solving data problems using data technologies.
• Experience with Hadoop, Hive, HBase, Spark, Trino, or comparable distributed data systems.
• Experience designing and implementing data pipelines and large-scale data processing jobs.
• Experience writing, modifying, and reviewing high-quality, testable, and efficient code.
• Experience with data pipelines, ETL/ELT, data-quality frameworks, Java or Python, SQL, Git, and production troubleshooting.
• Experience developing unit, integration, and end-to-end tests with a focus on automation.
• Experience building and maintaining CI/CD pipelines and deploying applications using containerization and orchestration tools.
• Experience monitoring applications in production and troubleshooting issues using observability tools.
• Experience integrating AI or ML services into applications, where applicable.
• Experience collecting and analyzing metrics to guide optimizations and improvements.
• Experience partnering with stakeholders to clarify requirements and ensure deliverables meet business needs.
• Experience applying secure coding practices and complying with regulatory standards.
• All roles require digital fluency, including the ability to work with emerging technologies such as Generative AI tools (e.g. ChatGPT, Microsoft Copilot) to support everyday work.

Nice to have

• 6 or more years of work experience with a Bachelor's Degree, or 4 or more years of relevant experience with an Advanced Degree (e.g. Masters, MBA, JD, MD), or up to 3 years of relevant experience with a PhD.
• Experience in solving data problems using data technologies.
• Experience with Hadoop, Hive, HBase, Spark, Trino, or comparable distributed data systems.
• Experience contributing in Open source components.
• Experience using or building AI agents and agentic patterns to improve development, testing, operations, troubleshooting, automation, onboarding, and documentation.
• Experience with data pipelines, ETL/ELT, data-quality frameworks, Java or Python, SQL, Git, and production troubleshooting.
• Experience with enterprise-class systems engineered for high availability, low latency, scalability, and supportability.
• Architecture depth across storage/compute separation, query and table formats, streaming, metadata, governance, and interoperability.
• Experience building and pushing code into production.
• Experience implementing and supporting real-time systems.
• Experience mentoring junior engineers and writing clear technical documentation.

Details

• Location: Bengaluru, India.