سرپرست مهندسی داده

Job Description

We are looking for a Senior Data Engineer to join our growing Data Infrastructure team. The hire will be responsible for expanding and optimizing our data ingestion pipeline architecture. The Data Engineer will support our data scientists and business intelligence on data initiatives and will ensure our optimal data infrastructure is consistent, stable, and robust throughout ongoing projects. She/he must be proactive and self-motivated supporting the data needs of multiple teams, systems, and products. The right candidate will be excited by the prospect of optimizing or even re-designing TAPSI’s data infrastructure architecture to support our next generation of products and data initiatives. Responsibilities: ● Create and maintain optimal data ingestion pipeline architectures. ● Assemble large, complex data sets that meet functional / non-functional business requirements. ● Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc. ● Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and big data technologies. ● Build analytics tools that utilize the data pipeline to provide actionable insights into customer acquisition, operational efficiency, and other key business performance metrics. ● Work with stakeholders including the Executive, Product, Data and Design teams to assist with data-related technical issues and support their data infrastructure needs. ● Create data tools for analytics and data scientist team members that assist them in building and optimizing our product into an innovative industry leader. ● Work with data and analytics experts to strive for greater functionality in our data systems. ● Lead innovation through exploration, benchmarking, making recommendations, and implementing big data technologies for platforms. ● Development and implementation of scripts for database maintenance, monitoring, performance tuning. ● Development of ETL routines in order to populate databases from sources and also to create aggregates. troubleshoots data issues within the business and across the business and presents solutions to these issues. ● Perform data updates, indexing, and maintenance in the application database.