Senior Data Engineer
Senior Data Engineer at BMC Software (Pune) who designs, builds, and scales enterprise data pipelines and cloud data platforms to power analytics, BI, ML, and Agentic-AI use cases. Core stack spans Snowflake, Databricks, BigQuery, Airflow, Python/Java/Scala, and ELT/ETL in a B2B SaaS setting.
- Compensation
- Not disclosed
- Location
- Pune
- Work setup
- Not specified
- Seniority
- Senior
- Employment
- Not specified
- Experience
- 5+ years
- Category
- Data engineering
- Posted
Skills
Must have
- Total experience of 5-10 years
- Strong background in B2B SaaS or enterprise technology environments
- Deep expertise in data architecture
- ELT/ETL development experience
- Cloud data platforms experience
- Data modeling and dimensional modeling
- Data quality, reliability, observability, and lineage
- Snowflake
- Databricks
- Google BigQuery
- Apache Airflow / data orchestration
- Python
- Java
- Scala
- SQL
- Informatica
- Data warehousing
- Machine learning / feature engineering support for AI and GenAI use cases
- Near real-time and batch data processing patterns
- CI/CD
- Data governance, security, and metadata management
- Cross-functional collaboration and communication
- Agile ways of working
Full description
Description and Requirements:
BMC empowers nearly 80% of the Forbes Global 100 to accelerate business value, faster than humanly possible. Our industry-leading portfolio unlocks human and machine potential to drive business growth, innovation, and sustainable success. BMC does this in a simple and optimized way by connecting people, systems, and data that power the world's largest organizations so they can seize a competitive advantage.
Total Experience : 5 - 10 years
We are seeking an experienced Senior Data Engineer to design, build, and scale modern data platforms and pipelines that power Agentic-AI, analytics, reporting, machine learning, and data-driven decision-making across the business. This role is ideal for someone with a strong background in B2B SaaS or enterprise technology environments, where data is critical to driving sales & product insights, revenue operations, customer success, and executive reporting.
The ideal candidate brings deep expertise in data architecture, ELT/ETL development, cloud data platforms, data modeling, and data quality, along with a strong understanding of how to build reliable, scalable, and governed data solutions in fast-paced technology organizations. This person will partner closely with analytics, data science, business teams, and platform stakeholders to ensure trusted data is delivered efficiently and at scale.
How you will contribute :
- Design, build, and maintain scalable data pipelines and integrations across internal and external systems.
- Develop and optimize data solutions that support analytics, BI, machine learning, AI/Agentic AI, operational reporting, and self-service data access.
- Build robust ELT/ETL workflows to ingest and transform data from systems such as CRM, product telemetry, marketing, finance, support, and subscription platforms.
- Design and maintain clean, scalable, and well-documented data models for enterprise reporting and analytics use cases.
- Improve data reliability, quality, observability, lineage, and performance across the data platform.
- Design and maintain scalable data pipelines and data services that enable AI/ML and GenAI use cases, including model-ready datasets, feature pipelines, and support for retrieval-based and intelligent application workflows.
- Partner with analytics engineers, data scientists, architects, and business stakeholders to translate requirements into production-grade data solutions.
- Ensure data pipelines are secure, governed, and aligned with enterprise data standards and best practices.
- Optimize data processing and storage for performance, cost, scalability, and maintainability.