Senior Data Engineer (Hybrid - 3 Days in Office)

At Freddie Mac, you will do important work to build a better housing finance system and you’ll be part of a team helping to make homeownership and rental housing more accessible and affordable across the nation.

Position Overview

The Senior Data Engineer will be part of the Freddie Mac's Enterprise Risk Business Technology Office. This team is responsible for partnering with the Enterprise Risk and Compliance organizations to define strategies, roadmaps, objectives, and deliver capabilities that transform the businesses. This role will be responsible for supporting our organization’s data-driven initiatives, collaborating with business partners and multi-discipline technology teams, and designing and implementing data modeling solutions! This position requires strong experience in data analysis, modeling and engineering with ability to translate complex technical issues into easily understood communications that will influence executive audiences with varied technical backgrounds and capabilities.

Our Impact:

• Delivery of Enterprise Risk Management solutions and data to optimally assess and track all risks, issues, controls, and compliance.

• Delivery and support of solutions for common Enterprise Risk Management (ERM) data platform to enable effective ERM data analytics and reporting

• Adoption of FHFA comprehensive Regulatory Reporting modifications and resolution of outstanding data quality issues

• Model data to deliver reports and provide business with information and data needed to drive efficiency t and support self-service analytics

• Architect data integrations between ERM and other systems

• Present historical data clearly to facilitate strategic decisions

Your Impact:

• Business requirements gathering and solutioning in alignment with enterprise business data strategy

• Architecting and documenting data warehouse solutions using data modeling

• Design, implement, and optimize end-to-end data pipelines for ingesting, processing, and transforming large volumes of structured and unstructured data.

• Assist team with finding patterns and relationships in data and identifying opportunities to monitor data quality

• Analyze and resolve data issues

• Evaluate and implement data storage solutions, including relational databases, NoSQL databases, data lakes, and cloud storage services.

• Build and maintain integrations with internal and external data sources and APIs.

• Monitor system performance, troubleshoot issues, and implement optimizations to enhance reliability and efficiency.

Qualifications:

• Bachelor’s degree in computer science, information technology or related field; advanced studies/degree preferred.

• 5 years’ extensive knowledge and experience in the Data technologies for Data Analytics, Data Lake/Mart/Warehouse, Databases SQL/NoSQL (DB2, Oracle, Sybase, Mongo, Postgres), Big Data Technologies (Spark or PySpark), ETL (Informatica, Talend), CDC (Attunity), REST API, Integration/EAI technologies like Informatica

• 3+ years’ experience in BI tools (MicroStrategy/Tableau), Data Management tools

• 3+ years’ experience with Technologies including Web Service API, XML, JSON, JDBC, Java, Python.

• 3+ years working with SaaS platforms such as Snowflake, Collibra, Mongo/MongoDB Atlas,

• Knowledge of enterprise data models, information classification, meta-data models, taxonomies and ontologies.

• Exposure to Full stack enterprise application development(Agular, Spring Boot, Automation testing using Selenium, cucumber)

• 5-7 years’ experience in a logical/physical data modeling, data architecture, data analysis, and data management role

• Experience with data modeling tools like ERwin, ER/Studio or Power Designer

• Experience with different query languages such as PL/SQL, T-SQL, and ANSI SQL

• Experience with database technologies such as Oracle, DB2, Sybase, PostgreSQL, Snowflake, S

• Server, MySQL, and AWS cloud databases

• Knowledge of data warehousing and business intelligence concepts including data mesh, data fabric, data lake, data warehouse, and data marts

• Risk and GRC products experience preferred

Keys to Success in this Role:

• Ability to operate as a self-motivated, pro-active, and result-driven problem solver with excellent analytical and interpersonal skills

• Quick learner of new technologies, tools, concepts and ability to translate them to challenge the status quo

• Excellent problem-solving skills and attention to detail

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