Posted on: 31/10/2026
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.
- Support near real-time and batch data processing patterns as required by business use cases.
- Contribute to the design of the overall data architecture, including ingestion, transformation, orchestration, storage, semantic modeling, and data serving layers.
- Troubleshoot pipeline issues, resolve data inconsistencies, and drive root-cause remediation.
- Contribute to engineering standards, code quality, and team best practices.
Skills :
- Analytics
- Artificial Intelligence
- Business Intelligence
- Business-to-business
- Communication
- Computer Science
- Data Architecture
- Data Modeling
- Data Processing
- Data Quality
- Data Warehousing
- Design
- Dimensional Modeling
- Engineering, Extract
- Transform
- Load
- Finance
- Informatica
- Java
-Machine Learning,
- Marketing
- Modeling
- Optimization
- Pipelines
- Computer Programming,
- Python,
- Reliability,
- Remediation,
- Reporting,
- Structured Query Language
- Scala, Scalability
- Software as a Service
- Storage
- Telemetry
- Troubleshooting
- Decision Making
- Agile
- Confidence
- Data Engineering
- Observability
- Snowflake
- Apache Airflow
- Continuous Integration/Continuous Delivery
- Data Platform
- Databricks
- Unstructured Data
- Customer Success
- Governance
- Baseboard Management Controller
- Use Cases
- Cross-functional Collaboration,
- Information Systems
- Musical Orchestration
- Feature Engineering
- Scale
- Data Orchestration
- Data Products
- Data Access
- Cloud Data Platforms
- Technology
- Google BigQuery
- Semi-structured Data
- Operational Reporting
- Maintainability
- Metadata Management
- Constituent Relationship Management
- Data Availability
Our commitment to you :
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Posted by
Posted in
Data Engineering
Functional Area
Data Engineering
Job Code
1681593