Data Engineer

Key Responsibilities:
 Develop, construct, test and maintain architectures
 Align architecture with business requirements
 Data acquisition
 Develop data set processes
 Use programming language and tools
 Identify ways to improve data reliability, efficiency and quality
 Conduct research for industry and business questions
 Use large data sets to address business issues
 Deploy sophisticated analytics programs, machine learning and statistical methods
 Prepare data for predictive and prescriptive modeling
 Find hidden patterns using data
 Use data to discover tasks that can be automated
 Deliver updates to stakeholders based on analytics
 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 Any ETL Tool.
 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 Cloud.
 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.

Candidate Qualifications:
Business Knowledge/Technical Skills:
 Bachelor of Computer Science or Engineering
 2+ Years’ Experience
 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.

For experience Data engineer
 For experience Data engineer
 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