▷ Apply Now Data Engineer 2

Job Description

The Data Engineer II works on different projects of data engineering to support the use cases, data ingestion pipeline and identify potential process or data quality issues. The team also supports marketing analytic teams with analytical tools that enable our analytics and business communities to do their job easier, faster and smarter. The team brings together data from different internal external partners and builds a curated Marketing analytics focused data tools ecosystem. The Data Engineer plays a crucial role in building this ecosystem depending on the Marketing analytics communities need.

Essential Job Functions

- Collaboration - 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. Demonstrates analytical, interpersonal and professional communication skills. Learns quickly and works effectively individually and as part of a team.
- Process Improvement - 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. Provide automation help to analytical teams around data centric needs using orchestration tools, SQL and possibly other big data/cloud solutions for efficiency improvement.
- Project Support - Supports Sr. Specialist and Specialist 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.
- Data and Analytics - Answers and trouble shoots questions about data sets and analytical tools; Develops, maintains and enhances new and existing analytics tools/Frameworks to support internal customers/consumers. Ingests data from different sources, processes it according to the requirement document in order to store data to Hive or NoSQL database or different warehousing solutions. Manages data coming from different sources, involved in HDFS maintenance, and loading of structured and unstructured data. Applies knowledge in Agile Scrum methodology that leverages the Client BigData platform and used version control tool Git. Imports and exports data using Sqoop from HDFS to RDBMS and vice-versa. Demonstrates an understanding of Hadoop Architecture and underlying Hadoop framework including Storage Management. Creates POCs to ingest and process streaming data using Spark and HDFS. Work on back-end using Scala, Python and Spark to perform several aggregation logics.
- Technical Skills - 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 DataFactory, Azure Functions and Databricks. Utilize basic knowledge of Rest API for designing networked applications.

Reports to: Lead or above

Working Conditions/Physical Requirements: Normal office environment

Direct Reports:

Minimum Requirements:

- Degree Required: Bachelor's Degree
- Area of Study: Computer Science, Engineering
- Years of Work Experience Required: Two to five years or more
- Type / focus of work experience required: Data Analytics