• Working SQL knowledge and experience working with relational databases, query authoring (SQL) as well as working familiarity with a variety of databases.
• 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 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.
• Experience in Data engineering

Good to have Skills:

• Hive, Spark, SQL

Experience: 3-10 Years

Job Location: Noida, Bangalore

Work Timings: General shift

Roles and Responsibilities

• 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 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.
• Create data tools for analytics and data scientist team members that assist them in building and optimizing our product