● 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.
Requirements: -
● Advanced 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 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 Cassandra.
○ Experience with data pipeline and workflow management tools: Azkaban,
Luigi, Airflow, etc.
○ Experience with AWS cloud services: EC2, EMR, RDS, Redshift
○ Experience with stream-processing systems: Storm, Spark-Streaming, etc.
○ Experience with object-oriented/object function scripting languages: Python,
Java, C++, Scala, etc.
4 Years 
50,000 - 80,000 Per Month 
Delhi
Safety Tips
How to get a Job early? Follow these tips
Jobs By Roles
Jobs By Cities
