Job at a glance
Responsibilities ● Create and maintain optimal data pipeline architecture. ● Assemble large, complex data sets that meet functional / non-functional business requirements. ● Building and optimizing ‘big data’ data pipelines, architectures and data sets. ● Maintain, organize & automate data processes for various use cases. ● Identifying trends, doing follow-up analysis, preparing visualizations.
● Creating daily, weekly and monthly reports of product KPIs. ● Create informative, actionable and repeatable reporting that highlights relevant business trends and opportunities for improvement. Required Skills And Experience: ● 2-5 years of work experience in data analytics- including analyzing large data sets. ● BTech in Mathematics/Computer Science ● Strong analytical, quantitative and data interpretation skills.
● Hands-on experience with Python, Apache Spark, Hadoop, NoSQL databases(MongoDB preferred), Linux is a must. ● Experience building and optimizing ‘big data’ data pipelines, architectures and data sets. ● Experience with Google Cloud Data Analytics Products such as BigQuery, Dataflow, Dataproc etc. (or similar cloud-based platforms). ● Experience working within a Linux computing environment, and use of command-line tools including knowledge of shell/Python scripting for automating common tasks.
● Previous experience working at startups and/or in fast-paced environments. ● Previous experience as a data engineer or in a similar role.