We are looking for a passionate Data Engineer to join our team. You will work closely with other teams like data analytics, marketing, data science and individual product teams to specify, validate, prototype, scale, and deploy data pipelines features and data architecture.

Ability to work in a fast-paced startup mindset. Should be able to manage all aspects of data extraction transfer and load activities.
Develop data pipelines that make data available across platforms.
Should be comfortable in executing ETL (Extract, Transform and Load) processes which include data ingestion, data cleaning and curation into a data warehouse, database, or data platform.
Work on various aspects of the AI/ML ecosystem – data modeling, data and ML pipelines.
Work closely with Devops and senior Architect to come up with scalable system and model architectures for enabling real-time and batch services.

Ideal Candidate

5+ years of experience as a data engineer or data scientist with a focus on data engineering and ETL jobs.
Well versed with the concept of Data warehousing, Data Modelling and/or Data Analysis.
Experience using & building pipelines and performing ETL with industry-standard best practices on Redshift (more than 2+ years).
Ability to troubleshoot and solve performance issues with data ingestion, data processing & query execution on Redshift.
Good understanding of orchestration tools like Airflow.
Strong Python and SQL coding skills.
Strong Experience in distributed systems like spark.
Experience with AWS Data and ML Technologies (AWS Glue,MWAA, Data Pipeline,EMR,Athena, Redshift,Lambda etc).
Solid hands on with various data extraction techniques like CDC or Time/batch based and the related tools (Debezium, AWS DMS, Kafka Connect, etc) for near real time and batch data extraction.

Perks, Benefits and Work Culture