Job Details

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.
• ct 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.

• 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
• dvanced 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:
  • Data mining/programming tools (e.g. SAS, SQL, R, Python)
  • Database technologies (e.g. PostgreSQL, Redshift, Snowflake, Greenplum)
  • Data visualization (e.g. Tableau, Looker, MicroStrategy)
• 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:
  • WS certification
  • Spark Streaming
  • Kafka Streaming / Kafka Connect
  • ELK Stack
  • Cassandra / MongoDB
  • CI/CD: Jenkins, GitLab, Jira, Confluence other related tools