Data Engineer - Starcom consulting limited

Interview Process: 3 Rounds of Interview



Expertise:

5-9+ years of relevant industry experience with a BS/Masters, or 2+ years with a PhD

Experience with distributed processing technologies and frameworks, such as Hadoop, Spark, Kafka, and distributed storage systems (e.g., HDFS, S3)

Demonstrated ability to analyze large data sets to identify gaps and inconsistencies, provide data insights, and advance effective product solutions

Expertise with ETL schedulers such as Apache Airflow, Luigi, Oozie, AWS Glue or similar frameworks

Solid understanding of data warehousing concepts and hands-on experience with relational databases (e.g., PostgreSQL, MySQL) and columnar databases (e.g., Redshift, BigQuery, HBase, ClickHouse)

Excellent written and verbal communication skills

A Typical Day:

Design, build, and maintain robust and efficient data pipelines that collect, process, and store data from various sources, including user interactions, financial details, and external data feeds.

Develop data models that enable the efficient analysis and manipulation of data for merchandising optimization. Ensure data quality, consistency, and accuracy.

Build scalable data pipelines (SparkSQL Scala) leveraging Airflow scheduler/executor framework

Collaborate with cross-functional teams, including Data Scientists, Product Managers, and Software Engineers, to define data requirements, and deliver data solutions that drive merchandising and sales improvements.

Contribute to the broader Data Engineering community at Airbnb to influence tooling and standards to improve culture and productivity

Improve code and data quality by leveraging and contributing to internal tools to automatically detect and mitigate issues.

Skill Sets - Python, SQL (expert level), Spark and Scala (intermediate).