Data Engineer

Job Summary

The Data Engineer will be responsible for evolving data infrastructure and data analytics capabilities. This role will build high quality, architecturally-sound systems that will transform ways to take advantage of data. This includes data infrastructure and pipelines to support analytics and product, as well as data science team. The Data Engineer will take ownership of a variety of areas in the data stack and lead the team forward.

This role will be impactful on the direction of the organization and be a part of building infrastructure from the ground up. The Data Engineer will take a prominent role in leading full stack development projects, collaborating with cross-functional teams to design, develop, and implement software solutions and API interfaces. Leverage your growing expertise to ensure seamless integration and optimal performance throughout the software development lifecycle (SDLC).

• Collaborates with internal/external stakeholders to manage data logistics – including data specifications, transfers, structures, and rules. Collaborates with business users, business analysts and technical architects in transforming business requirements into analytical workbenches, tools and dashboards reflecting usability best practices and current design trends.
  
  - (15%)
• Demonstrates analytical, interpersonal and professional communication skills. Learns quickly and works effectively individually and as part of a team. Accesses, extracts, and transforms Credit and Retail data from a variety of sources of all sizes (including client marketing databases, 2nd and 3rd party data) using Hadoop, Spark, SQL, Big data technologies etc.
  
  - (15%)
• Provides automation help to analytical teams around data centric needs using orchestration tools, SQL and possibly other big data/cloud solutions for efficiency improvement.
  
  - (10%)
• Supports Data Engineer and Sr. Data Engineer in new analytical proof of concepts and tool exploration projects. Effectively manages time and computing resources in order to deliver on time/correctly on concurrent projects. Involved in creating POCs to ingest and process streaming data using Spark and HDFS.
  
  - (10%)
• Answers and troubleshoots questions about data sets and analytical tools;
  Develops, maintains and enhances new and existing analytics tools/Frameworks to support internal customers/consumers. Design, develop and implement data infrastructure and pipelines that collect, connect, centralize, and curate data from various internal and external data sources.
  
  - (10%)
• Create automation systems and tools to configure, monitor, and orchestrate our data infrastructure and our data pipelines. Ingests data from different sources, processes it according to the requirement document in order to store data to Hive or No
  
  SQL database or different warehousing solutions. Involved in HDFS maintenance, and loading of structured and unstructured data.
  
  - (10%)
• Develop and manage scalable ETL pipelines to integrate data from diverse sources into the organization’s data systems, ensuring high performance and reliability. Create efficient data pipelines using tools like Azure Data Factory, Databricks, and AWS, focusing on data quality, integrity, and timely delivery to all data users.
  
  - (10%)
• Participate in Agile/Lean methodologies and Dev Ops practices to ensure seamless integration and deployment of data solutions. Assist in designing and maintaining data infrastructure, including Snowflake and other cloud-based solutions, adhering to best practices and enterprise architecture guidelines.
  
  - (10%)
• Expert in writing complicated SQL Queries and database analysis for good performance. Experience working with python or Scala, Spark, Hadoop, Hive, Oozie, Sqoop, HDFS, Impala, Shell Scripts, Microsoft Azure Services like ADLS/Blob Storage solutions, Azure Data Factory, Azure Functions and Databricks. Utilizes basic knowledge of Rest API for designing networked applications.
  
  - (10%)

• Bachelor’s Degree in Computer Science or Engineering; or equivalent technical training and experience.
• 2+ years of experience in Data & Analytics.
• 2+ years of experience and proficient with…