Data Engineer
Core
Design and deliver secure, stable, scalable data collection, storage, access, and analytics solutions; develop and maintain mission-critical data pipelines and architectures.
Role type
Senior Data Engineer (Data Platform & Pipelines)
Builds
Enterprise data models, large-scale data processing pipelines, and analytics solutions for a Consumer and Community Bank.
Domain
Financial Services / Data Engineering
Required skills
Python, PySpark, SQL, NoSQL (Cassandra, DynamoDB, MongoDB), AWS, Data Lakehouse (Databricks, Hadoop), Data Warehousing (Snowflake, Redshift), Orchestration (Airflow, Step Functions), Data Modeling (Dimensional, Data Vault, Kimball, Inmon), Unix scripting, Big Data formats (Parquet, Iceberg), Streaming/Batch processing.
Preferred skills
Gen AI models via APIs/SDKs, Data governance and security best practices, Data analysis for business insights, Agile practices, TDD/BDD, CI/CD toolsets.
Technologies
Airflow, AWS, Redshift, Cassandra, Databricks, Hadoop, JSON, MongoDB, Oracle, Python, PySpark, SQL, Snowflake, Spark, Unix
Responsibilities
Design and deliver secure, stable, scalable data collection, storage, access, and analytics solutions; develop, test, and maintain mission-critical data pipelines and architectures; review data protection controls; make tailored configuration updates in tools; update logical and physical data models; use SQL extensively and apply NoSQL technologies; build and maintain enterprise data models and large-scale data processing pipelines; lead code reviews and mentor fellow team members; improve data quality and make data more accessible for analysts and data scientists; ensure solutions align with data governance standards and broader business objectives.
Seniority
Senior (Level III), hands-on IC with mentorship