Data Engineer

Experience Required

• 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.
  

• 3+ 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.
  

• Work with cutting-edge technologies on high-impact systems.
• Be part of a collaborative and technically driven team.
• Enjoy flexible work options and a culture that values learning.
• Competitive salary, benefits, and growth opportunities.