Senior Data Engineer

Experian is the world's leading global information services company, unlocking the power of data to create more opportunities for consumers, businesses and society. We are thrilled to share that FORTUNE has named Experian one of the 100 Best Companies to work for. Also, for the last five years we've been named in the 100 "World's Most Innovative Companies" by Forbes Magazine. With a focus on our employees, we have been certified for the third time as Great Place To Work (GPTW). Experian Consumer Information Services is redefining the way our clients do business within the customer credit lifecycle. Fueled by the best data and technology we help businesses make smarter decisions, identify consumers, make decisions on loans, market to prospects and collect.

Experian is looking for a Senior Data Engineer to help support Experian Housing and Verification business (EVH). Housing is a growing business within Experian ecosystem and provides solutions for all aspects of mortgage lifecycle including prospecting, loan origination, loan servicing, risk management, and capital markets.

The Senior Data Engineer will help expand and enhance our data ecosystem, manage our Data Lake and ensure efficient flow and quality of data. Your role will involve integrating new and varied datasets, including publicly available ones, managing data architecture, ensuring data quality, and collaborating with platform and infrastructure teams to maintain seamless data operations. You will have a background in computer science and data engineering, with a focus on data integration, quality control, and advanced data processing techniques in a cloud environment.

You will evaluate and incorporate new datasets into our ecosystem, perform multimodal mapping across multiple datasets to ensure consistency and accuracy, and conduct rigorous quality control across heterogeneous datasets. You will develop and maintain efficient data pipelines and ETL processes, ensuring smooth data flow automation, and accessibility for analysis. Additionally, you will implement data governance best practices to uphold data integrity and security, troubleshoot and resolve data-related issues, and provide technical guidance and mentorship to data engineers. Staying updated on industry trends and new technologies will be essential as you try to improve our data engineering practices.

Main Responsibilities:

• Data Integration: Lead the integration of new and varied datasets into the data ecosystem, ensuring seamless data flow and accessibility.
• Collaboration: Work with platform and infrastructure teams to design and implement data solutions that support our goals.
• Data Pinning and Matching: Perform data pinning and matching to ensure consistency and accuracy across heterogeneous datasets.
• Quality Control: Conduct rigorous quality control checks to maintain high standards of data integrity and reliability.
• Data Pipeline Development: Develop, maintain, automate and increase data pipelines and ETL processes to ensure efficient data processing and transformation.
• Data Governance: Implement and enforce data governance best practices to ensure data security, compliance, and integrity.
• Troubleshooting: Identify, troubleshoot, and resolve data-related issues promptly to minimize disruptions.
• Technical Guidance: Be a liaison between business and technical teams to achieve project goals, delivering solutions.
• Innovation: Stay updated on industry trends and emerging technologies, seeking opportunities to improve data engineering practices and inspire creativity.

Reporting and Documentation: Prepare comprehensive documentation and reports on data processes, methodologies, and findings for internal and external stakeholders.

• Advanced degree preferably in a related quantitative field (Data Science, Computer Science, Math, Statistics, Engineering, Physics, or Economics).
• Experience communicating updates and resolutions to customers and other partners since, as a Data Engineer, you will collaborate with partners and technical teams.
• Minimum 8-10 years of work experience in data engineering and data design, and has expert knowledge working with SQL and data experience approaching a problem from different angles, analyzing pros and cons of different solutions
• Minimum 8-10 years of work experience in Python programming
• Minimum 4+ years of experience
• Minimum 5 years of experience with AWS data ecosystem (Redshift, EMR, S3, MWAA)
• Minimum 5 years of experience working in an Agile environment.
• Experience with Tableau or other data visualization tool.
• 2+ years of experience with Apache Airflow DAGs or equivalent tools (AWS MWAA) for the orchestration of data pipelines.
• Hands-on experience working and building with Python API-based data pipelines.
• Excellent knowledge in the Shell scripting

Our benefits include: Medical, life and dental insurance, Asociacion Solidarista, International Share Save Plan, Flex Work/Work from home, Paid time off, Annual Performance Bonus, Education Reimbursement, Family Bonding, Bereavement Leave, Referral Program, and more.

Experian is proud to be an Equal Opportunity and Affirmative Action employer. Innovation is a critical part of Experian's DNA and practices, and our diverse workforce drives our success. Everyone can succeed at Experian and bring their whole self to work, irrespective of their gender, ethnicity, religion, colour, sexuality, physical ability or age. If you have a disability or special need that requires accommodation, please let us know at the earliest opportunity.

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