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Data Engineer
at Zamp
22 days ago | 73 views | Be the first one to apply

Data Engineer


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 :

📍3+ years of experience in data engineering, with a strong focus on large-scale data platforms and data products. 📍Experience with big data technologies such as Hadoop, Spark, and Hive. Experience with natural language processing (NLP) tools and techniques. 📍Experience 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. 📍Understanding of Distributed Storage (HDFS/S3).Strong analytical/quantitative skills and comfortable working with very large sets of data. 📍Strong communication and interpersonal skills, with the ability to work effectively with a diverse range of stakeholders 📍Experience with integration of data across multiple data sources. 📍Good 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:

📍Collaborate with Engineers, analysts, Product Managers to understand their data needs and develop data solutions that meet those needs. 📍Design, build, and maintain scalable data platforms and pipelines to support the needs of the business. 📍Ensure data quality and accuracy by implementing data validation and testing process. 📍Work closely with DevOps to ensure that data solutions are deployed and operated effectively. 📍Stay up-to-date with emerging technologies and best practices in data engineering and recommend improvements to the data platform 📍Develop and maintain a data engineering roadmap, ensuring that the team is aligned with the company's overall goals and objectives .

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