Back
Tier-1 employer, Bangalore location, generalist data-engineer role with broad toolset increases competition.
Core data-engineering skills are transferable, but private markets and financial-data experience increase domain specificity.
Mandatory domain expertise and extensive technical stack (Python, Snowflake, cloud, Terraform, Kubernetes) cause high shortlisting strictness.
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Design and build scalable, production-grade data pipelines and analytics platforms to support private markets data products and analytics.
Own end-to-end data solution delivery—from translating business objectives to technical design, implementation, deployment, and production support.
Lead architectural decisions, set engineering standards, and engage senior stakeholders with clear communication of technical trade-offs and business impact.
Proven experience building scalable software systems for data workflows with expertise in Python, SQL, Snowflake, and Postgres.
Hands-on experience with modern software engineering tools: Git, CI/CD, automated testing, Docker, Kubernetes, and cloud platforms (AWS or Azure) including Infrastructure as Code (e.g., Terraform).
Demonstrated ability to design production-grade systems balancing performance, scalability, security, and maintainability.
Work Experience Required: Not explicitly mentioned in the JD.
Experienced senior engineer skilled at autonomous end-to-end technical ownership and architectural leadership in data engineering.
Strong technical communicator capable of translating complex concepts for business and cross-functional collaboration.
Technical background focused on scalable private markets data platforms supporting advanced analytics and AI/ML use cases in a regulated financial services environment.