About the company
Zamp is a financial technology company with a bold vision of reimagining the future of finance. Finance teams globally face manual, repetitive, and cumbersome tasks. We at Zamp want to empower them with time, calm, money, and joy, tackling harder problems. We foresee four key themes shaping the finance org of the future: Increased Connectivity: Fragmentation across banks, partners, and platforms complicates finance. We envision a seamlessly connected future, abstracting away complexity for real-time data access. AI Automation: Manual tasks like data transformation and reconciliation will be automated by intelligent AI agents, allowing teams to focus on strategic endeavours. Democratized Intelligence: AI-driven insights will be universally accessible, empowering better and faster decision-making, leading to exponential growth for companies. Evolving Financial Infrastructure: Regulatory-compliant advancements like real-time payments and blockchain technology will revolutionize financial exchange, driving efficiency and adaptation. Zamp, founded in 2022 by our experienced leader - Amit Jain, an IIT Delhi and Stanford graduate, and industry veteran with over 20 years of experience, previously held significant roles including Managing Director at Sequoia Capital and Head of Asia Pacific at Uber. Our seed funding round raised ~$22Mn from Sequoia Capital, Dara Khosrowshahi (CEO, Uber), Tony Xu (CEO, Doordash), Marcelo Claure (ex-CEO, Softbank International), and other prominent angel investors. At Zamp, we are excited about what the future holds. We are a team of dreamers, builders, product thinkers building for the new world!
Job Summary
What you need to be successful in the role :
š3+ years of experience in data engineering, with a strong focus on large-scale data platforms and data products. šExperience with big data technologies such as Hadoop, Spark, and Hive. Experience with natural language processing (NLP) tools and techniques. šExperience working with large-scale data and implementing scalable data architectures. Good Understanding of Apache Spark ,Data Frames, data Sets, RDDs, Spark SQL/PySpark/Scala APIs with deep understanding of Performance optimisations. šUnderstanding of Distributed Storage (HDFS/S3).Strong analytical/quantitative skills and comfortable working with very large sets of data. šStrong communication and interpersonal skills, with the ability to work effectively with a diverse range of stakeholders šExperience with integration of data across multiple data sources. šGood understanding of distributed computing principles. Good to have: Experience with Message Queues (e.g., Apache Kafka) Experience with MPP systems (e.g., Redshift/Snowflake/BigQuery).
You are likely to succeed in this role if you have experience in:
šCollaborate with Engineers, analysts, Product Managers to understand their data needs and develop data solutions that meet those needs. šDesign, build, and maintain scalable data platforms and pipelines to support the needs of the business. šEnsure data quality and accuracy by implementing data validation and testing process. šWork closely with DevOps to ensure that data solutions are deployed and operated effectively. šStay up-to-date with emerging technologies and best practices in data engineering and recommend improvements to the data platform šDevelop and maintain a data engineering roadmap, ensuring that the team is aligned with the company's overall goals and objectives .
