Responsibilities:

• Provide leadership to develop and execute highly complex and large-scale data structures and pipelines to organize, collect and standardize data to generate insights and addresses reporting needs
• Interpret and integrate advanced techniques to ingest structured and unstructured data across complex ecosystem
• Build and maintain technical solutions required for optimal ingestion, transformation, and loading of data from a wide variety of data sources and large, complex data sets with a focus on healthcare related data
• Develop data profiling and data quality methodologies and embed them into the processes involved in transforming data across the systems
• Manages and influences the data pipeline and analysis approaches, uses different technologies, big data preparations, programming and loading as well as initial exploration in the process of searching and finding data patterns
• Provide strategic analytics and counseling to management on important database technology practices
• Leads and implements ongoing data modelling activities, oversees and directs changes to the data models and associated DDL
• Conducts and facilitates data modeling and data engineering solutions to solve business needs and translates business requirements into data products and services
• Leads the development of technical roadmaps and approaches for data analyses to find patterns, to design data models, to scale the model to a managed production environment within the current or a new technical landscape
• Responsible for building, deploying, and ensuring all database infrastructure is available 24/7/365
• Experience with AWS and Databricks strongly preferred
• Leverage software development and automation to design, modernize, and deliver database infrastructure
• Develop automation and tooling to increase operational efficiency while ensuring system reliability and security
• Participates in setting the architectural direction for database platforms and projects
• Manage multiple competing priorities in a fast-paced, deadline-oriented environment
• Provide relevant insights of data store infrastructure through metrics, monitoring, and alerting
• Participate in live event support, root cause analysis and troubleshooting and on-call rotation
• May provide oversight and direction to junior team members
• Experience in healthcare or health Insurance helpful, but not mandatory
• Provide input to highly complex decisions that impact future enhancements
• Seek input from multiple constituents and stakeholders to drive innovative solutions
• Incorporate feedback and ensure decisions are implemented swiftly to yield high quality execution
• Effectively negotiate and resolve conflicts in a constructive manner
• Serve as a role model, demonstrating respect and inclusion, creating a culture that fosters innovation
• Support and mentor engineers, empowering them to make effective decisions

Requirements:

• 10+ years of experience working in data engineering role
• 10 years of experience with programming and database scripting
• 5 years of experience with AWS and Databricks strongly preferred
• Experience building a proper path to production leveraging multiple lifecycles, testing, integration, and CI/CD pipelines
• Experience running, deploying, and maintaining production cloud infrastructure in AWS
• Strong experience with ETL/ELT design and implementations in the context of large, disparate, and complex datasets
• Demonstrated experience with a variety of relational database and data warehousing technology such as AWS Redshift and Databricks
• Familiarity with Oracle, MySQL, and PostgreSQL to mainly support Commercial Off-the-Shelf (COTS) products, preferred but not required.
• Other tools used are Tivoli Work Scheduler (TWS) to load data from Databricks into Redshift.
• Cognos and SAS interaction with the data infrastructure
• Demonstrated experience with big data processing systems and distributed computing technology such as Spark, Streamsets, etc. desirable
• Experience with developing solutions on cloud computing services and infrastructure in the data and analytics space
• Prior experience with Data Engineering projects and large teams
• Experience operating within a database reliability engineering (DRE) and/or systems reliability engineering (SRE) role
• AWS Certification.
• Bachelor’s degree or higher in a quantitative discipline such as Statistics, Mathematics, Engineering, Computer Science, Econometrics, or information sciences such as business analytics or informatics

EEO Employer:

RELI Group is an Equal Employment Opportunity / Affirmative Action employer. All qualified applicants will receive consideration for employment without regard to race, color, national origin, ancestry, citizenship status, military status, protected veteran status, religion, creed, physical or mental disability, medical condition, marital status, sex, sexual orientation, gender, gender identity or expression, age, genetic information, or any other basis protected by law, ordinance, or regulation.

HUBZone:

RELI Group is an established SBA certified HUBZone and 8(a) small business. We encourage all candidates who live in a HUBZone to apply. You can check to see if your address is located in a HUBZone by accessing the SBA HUBZone Map.

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