Data Engineer

• Create and maintain the optimal data pipeline architecture.
• Build the infrastructure required for optimal extraction transformation and loading of data from a wide variety of data sources using leading ELT and ETL tools such as Airbyte SuperMetrics and similar tools.
• Assemble large complex data sets that meet functional / nonfunctional business requirements.
• Build analytics tools and dashboards that utilize the data pipeline to provide actionable insights into customer acquisition buying behavior and other key business performance metrics.
• Work with stakeholders Product Data and Development teams to assist with datarelated technical issues and support their data infrastructure needs.
• Organize the data to ensure cost efficiency fast retrieval and security through appropriate selection of availability zones and regions.
• Build processes and select appropriate technology to promote operational efficiency and help strengthen the market competitiveness of our product.

• Advanced knowledge of SQL should be able to write complex queries joining data from multiple sources and presenting a coherent view to the end user.
• Should have experience working with relational databases such as MS SQL Server MySQL and PostgreSQL. Should have working knowledge to set up a database restore from backup create read replicas etc.
• Some exposure to NoSQL databases such as MongoDB or Cassandra will be an advantage.
• Experience with free source and proprietary ELT and ETL tools such as Airbyte SuperMetrics or similar ones. Must have handson experience of building endtoend data pipelines for a production system pulling data from sources such as Shopify Facebook and Google Analytics into local data warehouses.
• Experience with data transformation using DBT or similar tools to shape the incoming data into the desired format. Should have the necessary analytical skills to work with the unstructured data and convert those into actionable insights.
• Exposure to workflow orchestration using Airflow or similar tools.
• Working knowledge of data warehousing tools such as Google BigQuery or Amazon Redshift.
• Having some exposure to writing functions using Python will be a plus.
• Having 4 years of experience as a Data Engineer or similar role.
• Engineering or equivalent degree from a reputed institute.

Industry

• Advertising Services

Employment Type

data engineering,pipeline,transformation,analytics,mongodb