Lead Data Engineer

As a Data Engineer, you will be responsible for designing and implementing next-generation data pipelines, analytics, and Business Intelligence solutions. You will manage various AWS resources such as RDS, EMR, MWAA, and Lambda. Your primary focus will be on developing high-quality data architecture and pipelines to support business analysts and data scientists. Collaborating with other technology teams, you will extract, transform, and load data from diverse sources. Additionally, you will work towards enhancing reporting and analysis processes by automating self-service support for customers. You should have a solid background with 7-10 years of data engineering experience, including expertise in data modeling, warehousing, and building ETL pipelines. Proficiency in at least one modern programming language, preferably Python, is required. The role entails working independently on end-to-end projects and a good understanding of distributed systems related to data storage and computing. Analyzing and interpreting data using tools like Postgres and NoSQL for at least 2 years is essential. Hands-on experience with big data frameworks such as Apache Spark, EMR, Glue, Data Lake, and BI tools like Tableau is necessary. Experience with geospatial and time series data is a plus. Desirable skills include collaborating with cross-functional teams to design and deliver data initiatives effectively. You will build fault-tolerant and scalable data solutions using cutting-edge technologies like Spark, EMR, Python, AirFlow, Glue, and S3. The role requires a proactive approach to continuously evaluate and enhance the strategy, architecture, tooling, and codebase to optimize performance, scalability, and availability.,