the ideal candidate will use their passion for big data and analytics to provide insights into the business covering a range of topics. they will be responsible for developing an in-house etl-driven toolchain and conducting both recurring as well as on-demand analyses for business users, research folks, and customers.
responsibilities
- build optimized spark-based data processing jobs to generate analytical models and
deploy them into airflow
- build analytical models and data models to align with product strategy
- understand the day-to-day issues that our business faces, by closely communicating
with stakeholders across the board
- build data pipelines to facilitate quality checks on datasets across the board; thereby
ensuring a seamless flow of high-quality data into the platform
- develop a diverse range of visualizations to convey complicated data in a
straightforward fashion, for both internal and external audiences
qualifications
- bachelor's or master's degree.
- 2 - 4 years of experience in the analytics/engineering domain.
- proficient in pyspark, sql (google bigquery, etc.), and ci/cd driven deployment
- proficient in big-data related toolkits, kubernetes and docker
- experience in working with the airflow orchestration engine.
- redash or tableau or powerbi or equivalent visualization tools.
- problem-solving skills
- strong communication/interpersonal skills