Data Tech Lead (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:

Are you a transformation champion? Are you passionate about technology transformations? Are you looking for a career that allows you to work with the latest and greatest technologies? Do you have demonstrable record of enabling enterprise change through architectural leadership?

The Freddie Mac Enterprise BTO Tech is seeking a Data Tech Lead who will be responsible for the development, modifications, execution and measurement of company data policies, standards and guidelines which affect immediate operations.

Our Impact:

• Provide solutions for finance data needs that align with Enterprise data strategy for consistency and quality.

• Create and Implement Data Governance working with the Business data team.

• Build various data solutions within the overall data platform strategy by defining and establishing the data architecture.

• Collaborate with other IT teams to advance our technical capabilities.

• Automate and optimize processes and technologies.

Your Impact:

• Scrum/agile based development and hands-on architecture in data science domain.

• Create information strategies around data quality, implementation of a future state data architecture, metadata and information governance.

• Lead large, strategic, cross-disciplinary business change efforts.

• Resolve problems or transactions, where expertise is required to interpret against policies, guidelines or processes.

• Analyze, guide, lead, develop, and maintain efficient data pipelines and ETL process for large-scale data integration.

• Collaborate with data analysts and other engineer to define data needs and build solution that drive business insights.

• Technical consultation to clients and IT management on technologies, architecture solution options with tradeoffs, alignment with standards and roadmaps.

• Architect, develop, test, and deploy code for data extraction, transformation and loading processes (ETL/ELT).

• Define and compare solutions to figure out optimal solutions for business needs.

• Provides guidance to business counterparts, customers, and management on requirements pertinent to the data and technical capability.

Qualifications:

• Bachelor’s degree in computer science or engineering, or equivalent experience; advanced studies/degree preferred.

• Strong proficiency (8+ yrs) in Python programing language (Nice to have: Scala, Java).

• Strong proficiency in spark SQL, SQL, gremlin, GraphQL and database management (Snowflake cloud-base warehousing).

• Strong experience with data processing frameworks, DataFrames, Apache Spark, Graph DBs

• Familiar with Data product platforms and data product modelling and design.

• Experience with cloud platform AWS (EMR, EKS, Lambda).

• Experience writing statistical and/or optimization programs to develop models and algorithms. Programming languages may include—but are not limited to—Python, R

• Strong analytical and problem-solving skills with a high level of attention to detail.

• 10-15 years of broad technology experience and knowledge across multiple disciplines such as application development, database SQL/NoSQL, infrastructure platform, security products, ETL products, rule engines, and Business Intelligence (BI) tools

• 10 years of hands-on experience in Data architecture with solutions applied to multiple large-scale enterprise systems.

• Extensive knowledge and experience in the Data technologies for Data Analytics, Data Warehouse, Data Mart, BI, Big Data (Hadoop, HBase, Hive), Databases SQL/NoSQL, ETL (Informatica, Talend, Sqoop), CDC (Attunity), REST API, Integration/EAI technologies like Informatica, BI tools (MicroStrategy/Tableau), Snowflake.

• 10 years’ experience with Technologies including Web Service API, Integration/EAI technologies like Informatica, XML, JSON, JDBC, SQL, Java, Python, R.

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

Keys to Success in this Role:

• Data and Architectural leadership with knowledge of both legacy and modern cloud-based data technologies and applications.

• Proven judgment with excellent decision-making skills and excellent analytical skills, ability to handle ambiguity and lead technical solutions.