Software Engineer – 8-10 years experience, Data Warehousing, cloud data platforms, database

Jobtailor; Hyderabad; On-site; INR 3,500,000 - 7,000,000; Full time

Job summary

Jobtailor in Hyderabad, India seeks a senior data engineer to design and optimize scalable data pipelines for corporate analytics. You will collaborate with data analysts and engineers to ensure unified data availability, quality, and governance across the organization.

The role requires 8–10 years in Data Warehousing, plus hands-on ETL tools (Informatica, DBT) and cloud data platforms (Snowflake). Proficiency in Python, SQL, and scripting is essential, as is experience with Kafka, Docker, and

Qualifications

• 8-10 years of experience in Data Warehousing (DWH) with strong ETL knowledge.
• Bachelor’s degree in engineering, technology, or related field is required.
• Experience with cloud data platforms and database technologies like Snowflake.
• Hands-on scripting and programming: Unix shell, Python, SQL.
• Experience in data modeling, database structures, and data virtualization.

Responsibilities

• Design, develop, and maintain scalable data processing platforms.
• Collaborate with analysts, engineers, and partners to ensure data availability and quality.
• Lead development and optimization of data pipelines.
• Integrate advanced technology for faster insights.
• Serve as a go-to expert for data analytics and modeling.
• Architect and stabilize transactional data pipelines for IT data teams.
• Build and optimize pipelines for analytical reporting and self-service reporting.
• Lead POCs with emerging technologies to enhance analytics platforms.
• Define and implement AI/ML use cases to deliver insights.
• Ensure high data quality, governance, and security best practices.
• Work cross-functionally to deliver end-to-end solutions.

Skills

Data warehousing

ETL design & development

Cloud data platforms

Python / SQL

Unix shell scripting

Kafka

Git / CI/CD / Agile

Docker / Kubernetes

REST APIs / microservices

Data modeling

RAG / MCP Server

Education

Bachelor’s degree in engineering or related field

Tools

Informatica

DBT

Snowflake DMF

Docker

Kubernetes

CI/CD tools

Git

Job description

Responsibilities

• Design, develop, and maintain scalable data processing platforms supporting Corporate Functional Data IT.
• Collaborate closely with data analysts, engineers, and key partners to ensure unified data availability, quality, and accuracy across the organization.
• Lead the development and optimization of multiple data pipelines.
• Integrate advanced technology for faster insights.
• Serve as a go-to expert for data analytics and modeling.
• Architect and stabilize transactional data pipelines for the Cisco IT Data team using a unified ingestion framework.
• Build and optimize pipelines for analytical reporting, self-service reporting, and data virtualization models tailored to consumer needs.
• Lead POCs with emerging technologies to enhance analytics platforms, ensuring efficiency and alignment with business metrics and canonical data models.
• Define and implement AI/ML use cases (e.g., NLP to SQL conversational agents) to deliver actionable insights and accelerate business growth.
• Ensure high data quality, consistency, and adherence to governance and security best practices.
• Work cross-functionally with analytics, engineering, and business teams to deliver end-to-end solutions.

Requirements

• Bachelor’s degree in engineering, Technology, or a related field.
• 8-10 years of experience in Data Warehousing (DWH) with strong understanding of ETL processes and tools.
• Expertise in cloud data platforms and database technologies: Snowflake etc.
• Strong experience with ETL tools: Informatica, DBT.
• Proficiency with any data quality & observability tools: Snowflake DMF.
• Experience with data streaming technologies: Kafka.
• Hands‑on scripting and programming skills: Unix shell Script, Python, SQL.
• Experience in Enterprise AI integrations: MCP Server, RAG.
• Experience in data modeling, designing database structures, and enabling varied data consumption models (virtualization, reporting, etc.).
• Proven ability to build, optimize, and maintain efficient, reusable, and reliable data pipelines.
• Familiarity with Git, CI/CD pipelines, and Agile development methodologies.
• Good understanding of object‑oriented programming, data structures, and algorithms.
• Knowledge of REST APIs, microservices architecture, and system integration.
• Experience with Docker, Kubernetes, and DevOps practices.