System One
Location
Herndon, VA | United States
Job description
Client builds and operates the largest and most advanced mortgage securitization platform in the world, supporting the Uniform Mortgage-Backed Security (UMBS) of Fannie Mae and Freddie Mac. Supporting 70% of the mortgage-backed securities in the market, they provide best-in-class single-family issuance, bond administration, disclosure, and tax services. The support a broad portfolio of products for our clients with full lifecycle management.
Responsibilities:
Job Information
Data/ML Engineer is responsible for solution engineering of enterprise scale data management best practices. This includes patterns such as - modern data integration frameworks, building of scalable distributed systems using emerging cloud-based data design patterns. This role will be responsible for developing data integration tasks in data and analytics space. This position will report to director of data management group under Data Operations organization. This is an individual performer role.
Key Job Functions
• Demonstrate expert ability in implementing data warehouse solutions using Snowflake.
• Building data integration solutions between transaction systems and analytics platform.
• Expand data integration solutions to ingest data from internal and external sources and to further transform as per the business consumption needs.
• Create security policies in Snowflake to manage fine grained access control
• Develop tasks for a multitude of data patterns, e.g., real-time data integration, advanced analytics, machine learning, BI and reporting.
• Lead POC efforts to build foundational AI/ML services for Predictive Analytics.
• Building of data products by data enrichment and ML.
• Be a team player and share knowledge with the existing team members.
Specialized Knowledge & Skills
• Expertise in real-time data solutions, good to have knowledge of streams processing, Message Oriented Platforms and ETL/ELT Tools.
• Strong scripting experience using Python and SQL
• Working knowledge of foundational AWS compute, storage, networking and IAM.
• Solid scripting experience in AWS using lambda functions. Good to have knowledge of Cloud Formation template. Overall experience with AWS services should be over three years.
• Hands on experience with popular cloud-based data warehouse platforms, viz. Redshift, Snowflake.
• Experience with one or more data integration tools viz. Attunity (Qlik), AWS Glue ETL, Talend, Kafka etc.
• Strong understanding of data security – authorization, authentication, encryption, and network security.
• Experience in building data pipelines with related understanding of data ingestion, transformation of structured, semi-structured and unstructured data across cloud services
Key Skills:
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