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Job Summary

Essential Job Functions

• Builds data pipeline for various data sources particularly from many external data sources. Works with other project team members to understand the use cases familiar with data sources provides recommendation on data ingestion processes complete data ingestion monitor and identify potential process or data quality issues. - (15%)

• 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 2ndand 3rdparty data) using Hadoop Spark SQL Big data technologies etc. - (10%)

• Provides automation help to analytical teams around data centric needs using orchestration tools SQL and possibly other big data/cloud solutions for efficiency improvement. - (5%)

• Supports Lead Data Engineer and Principal 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 trouble shoots 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 NoSQL database or different warehousing solutions. Involved in HDFS maintenance and loading of structured and unstructured data. - (10%)

• Evaluate new technologies for continuous improvements in Data Engineering. Collaborate closely with the product team to build out new data features. Work with the data analysts and scientists to implement descriptive forecasting and predictive algorithms and models using the latest technologies. Make technology decisions for our data infrastructure. - (10%)

• Consistently write production-ready code that is easily testable easily understood by other developers and accounts for edge cases and errors. Use systematic debugging to diagnose all issues located to a single service as well as cross service issues. Approach all engineering work with a security lens. Actively look for security vulnerabilities in the code and when providing peer reviews. - (10%)

• Provide technical leadership and guidance to junior team members fostering a collaborative environment for continuous learning and innovation. Translate complex technical subjects for diverse audiences ensuring alignment and understanding across technical and non-technical stakeholders. - (5%)

Minimum Qualifications

• Bachelors Degree in computer science or engineering; or equivalent technical training and experience.

• 5 years of experience building and deploying large-scale data processing pipelines.

• 5 years of experience with AWS Spark with Python/Scala SQL with Redshift Postgre SQL and Columnar Databases

• 5 years of experience with Workflow & pipeline systems with Airflow.

Preferred Qualifications

• Masters Degree in computer science computer engineering IT or another related field of study.

• 8 years of experience in Data & Analytics

• Experience with message-based loosely coupled architectures (e.g. Kafka).

• Experience developing systems intended for cloud deployments (AWS EKS lambdas etc.). DevOps experience. Experience with analytics platforms like Looker or Tableau.

Skills

• Structured Query Language (SQL)

• Azure

• Databricks

• Terraform

• Powershell

• Orchestration tools

• Spark SQL

• Scala (Programming Language)

• Python (Programming Language)

• PySpark

• NoSQL

• Linux Shell Scripting

• HBase

• Cloudera Impala

• Cloudera Data Platform (CDP)

• Big Data

• Apache Hadoop

Reports To: Manager and above

Direct Reports: 0

Work Environment

• Normal office environment hybrid.

Other Duties

This job description is illustrative of the types of duties typically performed by this job. It is not intended to be an exhaustive listing of each and every essential function of the job. Because job content may change from time to time the Company reserves the right to add and/or delete essential functions from this job at any time.

• All job offers are contingent upon successful completion of credit and background checks.

• Bread Financial is an Equal Opportunity Employer.

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