for candidate to be converted from contract to full time they need to be in Wilmington, DE / Baltimore, MD /Charlotte, NC / Dallas, TX / New York, NY / Evansville, IN.
The Lead Data Engineer will report to the Marketing Technology team and will support the development
of the customer-centric strategy to increase automation and the use of data and analytics throughout
the customer journeys. The candidate will be responsible for identifying relevant data and utilizing data
tools, technologies, and processes to develop continuous, data-driven, and automated customer
communications across marketing and servicing towards omni-channel personalized customer
experience vision and outcomes.
CORE RESPONSIBILITIES
Create and manage cloud resources in AWS.
Data ingestion from different data sources which exposes data using different technologies, such as
RDBMS, REST HTTP API, flat files, Streams, and Time series data based on various proprietary
systems.
Implement data ingestion and processing with the help of Big Data technologies.
Data processing/transformation using various technologies such as Spark and Cloud Services.
Understand the business logic and implement it using the language supported by the base data
platform.
Develop automated data quality check to make sure the right data enters the platform and verify
the results of the calculations.
Develop an infrastructure to collect, transform, combine, and publish/distribute customer data.
Define process improvement opportunities to optimize data collection, insights, and displays.
Ensure data and results are accessible, scalable, efficient, accurate, complete, and flexible.
Identify and interpret trends and patterns from complex data sets.
Construct a framework utilizing data visualization tools and techniques to present consolidated
analytical and actionable results to relevant stakeholders.
Act as a key participant in regular Scrum ceremonies with the Agile teams.
Demonstrate proficiency at developing queries, writing reports, and presenting findings.
Mentor junior members and bring best industry practices.
QUALIFICATIONS
5-7+ years experience as a data engineer in consumer finance or equivalent industry (e.g. consumer
loans, collections, servicing, optional product, insurance sales)
Strong background in math, statistics, computer science, data science, or related discipline
Advanced knowledge of at least one language: Java, Scala, Python, C#
Production experience with: HDFS, YARN, Hive, Spark, Kafka, Oozie / Airflow, Amazon Web Services
(AWS), Docker / Kubernetes, Snowflake
Proficient with:
o Data mining/programming tools (e.g. SAS, SQL, R, Python)
o Database technologies (e.g. PostgreSQL, Redshift, Snowflake, Greenplum)
Comfortable learning about and deploying new technologies and tools
Organizational skills and the ability to handle multiple projects and priorities simultaneously and
meet established deadlines
Good written and oral communication skills, and ability to present results to non-technical
audiences
Knowledge of business intelligence and analytical tools, technologies, and techniques
Familiarity and experience in the following is a plus:
o AWS certification
o Spark Streaming
o Kafka Streaming / Kafka Connect
o ELK Stack
o Cassandra / MongoDB
o CI/CD: Jenkins, GitLab, Jira, Confluence other related tools