Data Enginner

Location: Bangalore
Specialization: IT Software- E-Commerce / Internet Technologies
Sub Specialization:

Our Client is looking for data engineers to join our kick-ass engineering team. We are looking for smart, dynamic individuals to connect all the pieces of the data ecosystem.


About the Role:


What are we looking for:


1.         2+ years of development experience in at least one of MySQL, Oracle, PostgreSQL or MSSQL and with Big Data frameworks / platforms / data stores like Apache Drill, Arrow, Hadoop, HDFS, Spark, MapR etc

2.         Strong experience setting up data warehouses, data modeling, data wrangling and dataflow architecture on the cloud

3.         2+ experience with public cloud services such as AWS, Azure, or GCP and languages like Java/ Python etc

4.         2+ years of development experience in Amazon Redshift, Google Bigquery or Azure data warehouse platforms preferred

5.         Knowledge of statistical analysis tools like R, SAS etc

6.         Familiarity with any data visualization software

7.         A growth mindset and passionate about building things from the ground up and most importantly, you should be fun to work with


As a data engineer, you will:

1.         Create and maintain optimal data pipeline architecture,

2.         Assemble large, complex data sets that meet functional / non-functional business requirements.

3.         Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.

4.         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.

5.         Build analytics tools that utilize the data pipeline to provide actionable insights into customer acquisition, operational efficiency and other key business performance metrics.

6.         Work with stakeholders including the Executive, Product, Data and Design teams to assist with data-related technical issues and support their data infrastructure needs.

7.         Keep our data separated and secure across national boundaries through multiple data centers and AWS regions.

8.         Create data tools for analytics and data scientist team members that assist them in building and optimizing our product into an innovative industry leader.

9.         Work with data and analytics experts to strive for greater functionality in our data systems.