Senior Data Engineer

Designation : Senior Data Engineer

Experience : 6 to 10 years

Qualification : BE/B tech, ME/M tech, Bsc, Msc.

Location : Hyderabad, Bangalore and Mumbai

Job Description

As a Senior Data Engineer , you will own the end-to-end data platform, from raw data ingestion through transformation to trusted, business-ready datasets. You will be responsible for designing, building, and maintaining scalable, reliable, and high-quality data pipelines that power analytics and decision-making across the organization.

This role requires someone who can make sound architectural decisions, balance trade-offs, and deliver production-grade solutions in a fast-paced environment. You'll partner closely with analysts, engineers, and business stakeholders, ensuring data solutions are reliable, maintainable, and aligned with business needs. A strong bias for action, systems thinking, and expertise in modern data engineering practices are essential. Key Responsibilities

• Design, build, and maintain end-to-end data pipelines from ingestion to curated, trusted data models.

• Develop scalable and maintainable data transformation layers using modern transformation frameworks.

• Design and optimize data warehouse schemas and data models to support reporting and analytics.

• Write highly efficient, production-grade SQL and optimize complex queries for performance.

• Build, maintain, and monitor orchestration workflows, ensuring proper dependency management and data lineage.

• Implement data quality, validation, monitoring, and reliability practices to ensure trusted datasets.

• Make architecture and design decisions while balancing scalability, maintainability, and delivery speed.

• Collaborate closely with analysts, engineers, and business stakeholders to understand requirements and translate them into robust data solutions.

• Proactively identify improvements in data architecture, pipeline performance, and engineering practices.

• Leverage Large Language Models (LLMs) and AI-assisted development tools to improve engineering productivity and accelerate delivery.

• Build solutions that are production-ready, scalable, and resilient while maintaining high development velocity.

  Must-Have Skills

  Technical Skills

• Expert-level proficiency in SQL , including complex query optimization, performance tuning, and advanced data modeling.

• Strong expertise in data warehousing concepts , dimensional modeling, and analytical database design.

• Hands-on experience with modern data transformation frameworks such as:

  • dbt
  • SQLMesh

• Strong understanding of workflow orchestration, DAG design, dependency management, and data lineage.

• Experience designing and maintaining reliable, production-grade data pipelines.

• Strong knowledge of data quality frameworks, testing, validation, and monitoring.

• Excellent systems thinking with the ability to design scalable and maintainable data architectures.

• Proven ability to deliver high-quality solutions in fast-paced, agile environments.

  AI LLM Skills (Mandatory)

Demonstrated hands-on experience using Large Language Models (LLMs) as a core part of the software development lifecycle, including:

• Prompt engineering
• Context engineering
• Retrieval-Augmented Generation (RAG)
• Vector embeddings and vector search
• Token optimization and context management
• LLM evaluations and quality assessment
• Guardrails and hallucination mitigation
• Function calling, tool use, and AI workflow orchestration

Candidates should have practical experience integrating AI into engineering workflows rather than limited exposure or experimentation.

Professional Skills

• Strong communication and stakeholder management skills.

• Ability to challenge requirements constructively and provide technical guidance.

• Strong ownership mindset with the ability to make informed technical decisions independently.

• Bias toward execution, continuous improvement, and delivering business value.

  Nice-to-Have Skills

• Hands-on experience building and operating data platforms on Databricks .

• Experience with AI-assisted or "vibe coding" approaches to software development.

• Exposure to fintech, banking, payments, or financial services data platforms.

• Experience designing scalable data architectures in cloud-native environments.

• Familiarity with modern DevOps, CI/CD, Infrastructure as Code (IaC), and observability practices.

• Experience working in high-growth startups or small engineering teams with broad ownership.

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.