Data Engineer

Responsibilities for Data Engineer ● Create and maintain optimal data pipeline architecture. ● Assemble large, complex data sets that meet functional / non-functional business requirements. ● Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and AWS big data technologies including Glue, EMR, Lambda ● Develop and own Krishify Data pipeline and warehouses ● Build analytics tools that utilize the data pipeline to provide actionable insights into customer acquisition, operational efficiency and other key business performance metrics. ● Build our data centers for failover scenarios. ● Work with data and analytics experts to strive for greater functionality in our data systems. Qualifications for Data Engineer ● Advanced working SQL knowledge and experience working with relational databases, query authoring (SQL) as well as working familiarity with a variety of databases including Postgres, MongoDB, Bigquery. ● Experience building and optimizing big data data pipelines, architectures and data sets. ● Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement. ● Strong analytic skills related to working with unstructured datasets. ● Build processes supporting data transformation, data structures, metadata, dependency and workload management. ● A successful history of manipulating, processing and extracting value from large disconnected datasets. ● Working knowledge of message queuing, stream processing, and highly scalable ‘big data’ data stores. ● Strong project management and organizational skills. ● Experience supporting and working with cross-functional teams in a dynamic environment. ● We are looking for a candidate with 5+ years of experience in a Data Engineer role, who has attained a Graduate degree in Computer Science, Statistics, Informatics, Information Systems or another quantitative field. They should also have experience using the following software/tools: ○ Experience with big data tools: Hadoop, Spark, Kafka, etc. ○ Experience with relational SQL and NoSQL databases, including Postgres and MongoDB. ○ Experience with data pipeline and workflow management tools: Azkaban, Luigi, Airflow, etc. ○ Experience with AWS cloud services: EC2, EMR, RDS, Redshift, Lambda, Glue. ○ Experience with stream-processing systems: Spark-Streaming, Apache Flink etc. ○ Experience with object-oriented/object function scripting languages: Python, Java etc.