Production Support Engineer I

Overview

As a production support Engineer, I play a key role in architecting and delivering high-quality, scalable data solutions within Data Governance/ Management team that empower Saving and Membership's AI and machine learning initiatives. With deep expertise in building data pipelines, optimizing performance, and ensuring data integrity, I collaborate closely with cross-functional teams, including data owners, data stewards, data scientists, and business intelligence analysts, to meet strategic objectives.

• Support the configuration and ingestion of designated structured, unstructured, and semi-structured data repositories into capabilities that satisfy mission partner requirements. This will support a data analytics and DevOps pipeline to drive rapid delivery of functionality to Business units.
• Automate configuration management, leverage tools, and stay current on data extract, transfer, and load (ETL) technologies and services.
• Work under general guidance, demonstrate initiative to develop approaches to solutions independently, review architecture, and identify areas for automation, optimization, right-sizing, and cost reduction to support the overall health of the environment.
• Apply comprehension of data engineering-specific technologies and services. Leverage expertise in databases and a variety of approaches to structuring and retrieving data.
• Understand cloud architectural constructs and support the establishment and maintenance of cloud environments programmatically using vendor consoles.
• Engage with multiple functional groups to understand business units' challenges, prototype new ideas and technologies, help to create solutions, and design, implement, schedule, test, and deploy full features and components of solutions.
• Identify and implement scalable and efficient coding solutions.

Responsibilities

• As a production support Engineer, I play a key role in architecting and delivering high-quality, scalable data solutions that empower the organization's Analytics, AI and machine learning initiatives
• With deep expertise in building data pipelines, optimizing performance, and ensuring data integrity, I collaborate closely with cross-functional teams, including product owners, data scientists, and software developers, to meet strategic objectives
• Support the configuration and ingestion of designated structured, unstructured, and semi-structured data repositories into capabilities that satisfy mission partner requirements
• This will support a data analytics and DevOps pipeline to drive rapid delivery of functionality to the Business Units.
• Maintain all operational aspects of data transfers while accounting for the security posture of the underlying infrastructure and systems
• Monitor the health of the environment through a variety of tracking capabilities
• Automate configuration management, leverage tools, and stay current on data extract, transfer, and load (ETL) technologies and services
• Work under general guidance, demonstrate initiative to develop approaches to solutions independently, review architecture, and identify areas for automation, optimization, right-sizing, and cost reduction to support the overall health of the environment
• Apply comprehension of data engineering-specific technologies and services
• Leverage expertise in databases and a variety of approaches to structuring and retrieving data
• Understand cloud architectural constructs and support the establishment and maintenance of cloud environments
• Identify and implement scalable and efficient coding solutions
• Ensure all data governance workstreams are implemented for their Business Area (Program management; Policies, Standards, and Procedures; Metadata Management; Data Quality; Data Lifecycle Management) to ensure a streamlined data governance model is in place.
• Partner with stakeholders to implement information security standards and controls (e.g., encryption, RBAC).
• Drive root cause analysis on data quality issues identified and escalated from lines of business and IT. Lead the design and development of data audits and tools for the business data stewards. Train them in use of tools.
• Support execution of Enterprise Data Governance policies, standards, and procedures through technology
• Serve as an active member of data governance engagement and forums and provide expertise as needed for their business area.
• Drive compliance with established standards and metrics across the business area.

Qualifications

• Knowledge of and basic ability to use statistical techniques such as measures of central tendency, normal distribution, variance standard deviation, basic tests, correlation, and regression techniques to diagnose systems issues
• Basic knowledge of and the ability to leverage industry standard tools and practices such as Six Sigma, Lean Six Sigma and DevOps frameworks as needed
• Assist with developing or providing support for operationalized Analytics and AI solutions developed in Python, Spark or R in financial services, or similar, sector
• Assist with developing or providing support for Analytics and AI platforms used by large base of enterprise analytics teams and integrated into other core workflow and related systems
• Basic understanding of data warehousing, data cleaning, data pipeline processing and other techniques related to enterprise data usage
• Assist in support highly complex data processes and analytical models which support strategic business outcomes. Basic understanding of data models, large datasets, business/technical requirements, BI tools, data warehousing, statistical programming languages and libraries
• Basic knowledge of various data structures and the ability to extract data from various data sources, such as Cognos, Informatica and Mainframe
• Basic experience with data visualization tools such as Microsoft Power BI or Tableau
• Basic skill in building and supporting cloud enabled enterprise solutions leveraging Azure IaaS/PaaS ; Azure Data Catalog, Azure Data Lake, Azure Synapse, Machine Learning, Power BI, Apache Spark / Azure Databricks capabilities in financial services, or similar, sector
• Basic skill in using enterprise logging and monitoring tools such as Azure Log Analytics and KQL to develop complex queries to provide data driven operations support for Analytics & AI solutions in financial services, or similar, sector
• Basic skills in using tools such as Service Now, Azure Log Analytics and Azure Dev Ops to track and manage production issues
• Basic skill in using Help Desk tools such as ServiceNow to track and manage service issues for integrated cloud based analytics platforms
• Basic experience working within enterprise change management and/or excellent communication skills
• Bachelor's degree in Information Systems, Computer Science, Engineering, or related field, or the equivalent combination of education, training and experience

Desired Qualifications

• Knowledge of Navy Federal Credit Union instructions, standards, and procedures
• Master's degree in Information Systems, Computer Science, Engineering, or related field, or the equivalent combination of education, training and experience

Hours: Monday - Friday, 8:00AM - 4:30PM

Location: 820 Follin Lane, Vienna, VA 22180 | 5510 Heritage Oaks Drive, Pensacola, FL 32526 | 141 Security Drive, Winchester, VA 22602

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