Job Location: Mumbai
– Advanced SQL and relational databases, query authoring (SQL) as well as working familiarity with a variety of databases
– Strong analytic skills related to working with structured and unstructured datasets
– Performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement
– Manipulating, processing and extracting value from large disconnected datasets
– Build processes supporting data transformation, data structures, metadata, dependency and workload management
– Big data tools like Hadoop, Spark, Kafka, etc.
– Message queuing, stream processing, and highly scalable – big data- data stores
– Building and optimizing – big data- data pipelines, architectures and data sets
– Relational SQL and NoSQL databases, including Postgres and Cassandra
– Development of data pipeline and workflow management tools: Azkaban, Luigi, Airflow, etc.
– AWS cloud services: EC2, EMR, RDS, Redshift
– Stream-processing systems: Storm, Spark-Streaming, etc.
– Object-oriented/object function scripting languages: Python, Java, C++, Scala, etc.
– Visualization tools : Tableau, Power BI, Qlik etc.
As Data Engineer, your specific responsibilities include the following :
– Create and maintain optimal data pipeline architecture
– Assemble large, complex data sets that meet functional / non-functional business requirements
– Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.
– 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
– Build analytics tools that utilize the data pipeline to provide actionable insights into customer acquisition, operational efficiency and other key business performance metrics
– Work with stakeholders including the Executive, Product, Data and Design teams to assist with data-related technical issues and support their data infrastructure needs
– Keep our data separated and secure across national boundaries through multiple data centers and AWS regions
– Create data tools for analytics and data scientist team members that assist them in building and optimizing our product into an innovative industry leader
– Work with data and analytics experts to strive for greater functionality in our data systems
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