Hiring for a leading SAAS product company - Remote
Looking for a candidate with working experience in Data Engineering & Data Science who can able to lead and manage both teams.
#director #dataengineer #dataanalytics #etl #saas #ML #datascience #
5+ years of proven experience in areas of Analytics/Data Science/Data Engineering or Quantitative fields in the large scale environment
Guiding teams through planning, development, rollout, and migration.
Ability to translate data and technical concepts into requirements documents and user stories for Data engineering as well as Data Science.
Managing teams in rapid product development, including remote and offshore teams
Success building culture of innovation, ownership, accountability, and customer focus
Building and scaling a SaaS product
Good communication and presentation skills with ability to interact with different cross-functional teams varying levels
Ability to learn new tools and in data engineering and science.
Experience in creating enterprise scale data engineering pipelines, data-based decision-making, and quantitative analysis.
Knowledge in ETL/ELT data pipeline design, development and performance tuning in Big Data ecosystem.
Experience working with Data warehousing tools, including DynamoDB, SQL, Amazon Redshift, and Snowflake
Experience architecting data products in Streaming, Serverless and Microservices based Architecture and platform.
Exposure in building global scale cloud-native systems and modern tech stack: AWS, Java, Spring Framework, RESTful API, and container-based application.
Working knowledge of Data warehousing, Data modeling, Governance and Data Architecture
Experience of any industry standard ETL/workflow Tools (Mulesoft/Infa/Talend/airflow etc) and BI visualisation tools (Tableau, Looker etc)
Exposure in building Predictive models using machine learning through all phases of development, from design through training, evaluation, validation, and implementation.
Exposure with complex, high volume, multi-dimensional data, as well as AI/ML models based on unstructured, structured, and streaming datasets
Experience creating/supporting production software/systems and a proven track record of identifying and resolving performance bottlenecks for production systems.