Senior data Engineer
Revsure.ai is an early-stage US VC-backed company building and solving revenue visibility and confidence for revenue operations professionals – CRO, VP & Director of RevOps, and Analysts across the entire revenue cycle from marketing, to sales to customer success, for high growth B2B SaaS companies primarily in NA and Europe regions.
About the Founder
Deepinder Singh Dhingra is an industry veteran with over 20 years of experience building category-defining and unicorn B2B SaaS and software companies across Big Data Analytics, EnterpriseAI SaaS, Visual Analytics, Revenue Growth AI, and Advanced Business Planning.
About the Team and Role
The Data Platform team at RevSure AI is building an industry-first generic data model for storing and reporting on data from diverse sources systems that our customers use in tracking their end-to-end revenue life cycle. Our reporting layer is being built to power real-time querying of complex RevOps metrics in a multi-tenant ecosystem. Building all of this comes with interesting challenges in every aspect of data engineering including Data Modelling, Configurability of ETL pipelines, Entity Resolution, Metadata Management, Data Governance etc. The role requires solid understanding of data systems and ETL patterns to design and author complex data pipelines. Being an early member of the data team also provides a ton of learning opportunities and the chance to define and shape the architectural decisions involved in solving these challenges to help usher in a new era of Revenue Intelligence.
Experience and Skills
- Have 6+ years of experience with developing data applications using big data technologies such as Hadoop, Spark, Flink, Dataflow etc.
- Experience with workflow orchestration tools such as Airflow/Luigi/Azkaban etc.
- Experience with coding languages like Python/Java/Scala
- Experience with at least one cloud platform AWS/GCP/Azure
- Hands-on experience and highly advanced knowledge of SQL, Data Modeling, ETL Development, and Data Warehousing
- Experienced in scalable, configurable, parameterized, modular programming practices for data engineering.
- Knowledge and experience with Data Management and Data Storage best practices.
- Exposure to large databases, BI applications, data quality and performance tuning
- Good to have understanding of job management, resiliency
- Good to have prior experience with Graph, Time-series databases
Roles and Responsibilities
- Architect highly metadata-driven data pipelines with algorithms for data deduplication, data harmonisation, fuzzy matching, identity resolution
- Design and architect relational, time series and graph databases to run OLAP queries
- Design and develop SDKs and APIs to enable configurable data consumption paradigms
- Build tools to monitor the health of the data pipelines and data infrastructure
- Develop and lead the Data Engineering team
Full-time; Hybrid working - location: Bengaluru