Lead Data Engineer

4 weeks ago

Austin, United States Texas Department of Aging & Disability Services Full time
Job Description:
The Fraud Analytics unit within the Data Reviews Division of the Office of Inspector General (OIG) is responsible for performing innovative and advanced data analytics to detect fraud, waste and abuse in state health and human services programs such as Medicaid, the Childrens Health Insurance Program (CHIP), Supplemental Nutrition Assistance Program (SNAP) and Temporary Assistance for Needy Families (TANF) by supporting data-driven investigations, reviews, audits, and inspections.

Fraud Analytics seeks a motivated and talented Lead Data Engineer (Data Architect I) to contribute to the Fraud Analytics unit’s efforts to develop and implement algorithms, artificial intelligence/machine learning (AI/ML) models, and predictive analytics to generate insights and actionable leads to identify and respond to risks of fraud, waste, and abuse. This position reports to the Deputy Inspector General of Fraud Analytics and works under minimal supervision, with extensive latitude for the use of initiative and independent judgment. The Lead Data Engineer will work closely with Fraud Analytics data analysts and data scientists and will liaison and collaborate closely with the HHS Office of the Chief Data Architect and technology vendors.

The Lead Data Engineer will play a pivotal role in establishing and leading the data engineering efforts to support the Fraud Analytics team. This position will be responsible for designing, implementing, and maintaining scalable data pipelines, ensuring data quality and governance, and enabling advanced analytics capabilities for the OIG to support data-driven decision-making processes. The position will perform advanced data extract, transformation, and loading (ETL) work in support of the team’s work in developing and deploying algorithms and models that identify data trends, patterns, and anomalies. The Lead Data Engineer will also support data quality and data validation initiatives.

*** This position can telework % from and OIG location within Texas consistent with HHS telework policies. ***
Essential Job Functions:
Attends work on a regular and predictable schedule in accordance with agency leave policy and performs duties as assigned:

1. Designs, builds, and manages efficient, scalable, and reliable data pipelines to support ETL processes and data integration efforts; Extracts data from multiple sources and loads into a data warehouse, data store or other system to support analytics and data science use cases. Develops pipeline code and sets standards for related metadata management. Manages the data pipeline continuous integration and continuous delivery (CI/CD) processes. Manages data pipeline jobs throughout their lifecycle. Supports the task of deploying analytics and data science outputs into existing processes, applications, and dashboards. Develops and maintains a robust data architecture that supports the needs of data analysts and scientists, while ensuring security and compliance standards are met. (60%)

2. Leads the creation, implementation, and documentation of best practices and standards for data engineering within the Office of Inspector General. Works closely with data analysts, scientists, and other stakeholders to understand their data requirements and deliver the necessary data infrastructure and resources. Implement processes and tools to monitor, validate, and ensure the accuracy and integrity of data used for analysis. Assists in the identification and integration of potential new data sources. (20%)

3. Research and implement cutting-edge technologies and methodologies in data engineering to enhance the organization's data capabilities. Serves as a subject matter expert in health and human services and OIG program data. Serves as a liaison to departments and technology vendors. (15%)

4. Performs other duties necessary to achieve the mission of the Office of Inspector General. Statewide travel of about 5% may be required. (5%)

Knowledge Skills Abilities:
1. Knowledge of data engineering principles and practice; of cloud computing platforms (e.g., AWS, Azure, Google Cloud Platform (GCP), Snowflake) and their data services; of data modeling, data warehousing, data lake concepts and querying relational databases; of data wrangling, data storage, and data pipeline operations; of data governance and quality standards; of relational/non-relational data structures, theories, principles, and practices; of record keeping, including security procedures for handling, protecting, and distributing confidential data.

2. Expert skill in programming languages such as Python, Scala, or Java for ETL processes; using SQL to query and optimizing data queries to improve efficiency and reduce run times, especially in large, complex databases; data integration and ETL tools; and automating data collection and processing. Skill in Excel and PowerPoint.

3. Skill in critical thinking, analyzing problems, and devising effective solutions.

4. Skill in verbal and written communication skills essential to effectively interact with data analyst, data scientists, OIG customers, and OIG leadership.

5. Ability to design and implement complex data pipelines and architectures.

6. Ability to plan, organize, lead, manage and monitor data engineering projects from inception to completion.

7. Ability to adapt to rapidly changing technologies and methodologies.

8. Ability to effectively communicate complex data findings and analytical methodologies, both verbally and in writing, to technical and non-technical audiences.

9. Ability to work effectively in teams that may cross departments and/or agencies. Ability to mentor and support team members in data engineering practices.

10. Ability to work independently, exercise independent judgment, prioritize tasks, and manage multiple projects/assignments/responsibilities in a fast-paced environment under time constraints.

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