Cotiviti is a company focused on data management for clients, and they are seeking a Data Engineer. The role involves overseeing ETL processes, maintaining data pipelines, and ensuring data quality and security while collaborating with stakeholders to deliver high-quality data solutions.
Responsibilities:
- Oversee ETL processes to ensure their success, with the primary responsibility of providing accurate and timely data across various products to support the company's revenue generation
- Maintain data pipelines running on proprietary big data processing platform and providing support to make sure data delivery SLAs are met
- Maintain data engineering processes using a variety of tools including T-SQL, Spark and Scala, and shell scripting. Generally focused on data ingestion for healthcare data management, data validation, statistical report generation, and program validation
- Develop, support, and improve scalable and efficient data ingestion processes and techniques aimed at enhancing process efficiencies and optimizing query performance for our proprietary data applications and systems
- Implement and perform data validation and quality checks to maintain high data integrity
- Perform troubleshooting, data analysis, data mining, investigations and identifying root cause of issues using several cutting-edge data analysis tools in a fast-paced environment
- Collaborate with stakeholders to understand data requirements and deliver high-quality data solutions
- Work with Technical Operations to troubleshoot complex database issues related to the entire environment including OS, storage, and servers
- Provide off hours support to resolve production issues when necessary
- Develop data transformation specifications to convert source data to be loaded into target data warehouse tables using SQL and other Data Integration/ETL tools
- Support the implementation of data governance policies and security measures to protect sensitive information
- Create and maintain dashboards as needed
- Participate in meetings with clients and/or stakeholders
- Complete individual productivity tracking
- Complete task assignments using department ticketing system within assigned deadline
- Achieve organizational and individual goals as identified in performance reviews and goal setting exercises
- Complete all special projects and other duties as assigned
- Must be able to perform duties with or without reasonable accommodation
Requirements:
- Bachelor's degree in Computer Science, Information Technology or equivalent work experience
- 2+ years of working knowledge of RDBMS (Oracle, MS SQL, Vertica, etc.) and experience using SQL, PL/SQL or other data integration/ETL tools
- 2+ years of experience in data engineering, data analysis, or a related field with a strong track record of building and managing data pipelines
- 2-4 years' experience with data aggregation, standardization, linking, quality check mechanisms, and reporting
- 2-4 years' experience with big data technologies like Hadoop and Spark
- Proficient and experienced in analyzing, designing, and developing solutions and strategies involving relational databases (e.g., Oracle, Vertica, SQL Server), ETL tools (e.g., SSIS, ODI, Informatica), and data warehousing concepts
- Solid understanding of Linux environments; strong knowledge of shell scripting and file systems
- Ability to analyze data with a high level of detailed accuracy, identify root causes of issues, and demonstrate problem-solving skills to troubleshoot data-related issues
- Experience in coding principles and the ability to follow best practices for developing and deploying code for data manipulation and automation
- Experience in at least one programming language such as Python, Java, Scala or Powershell
- Proficient in Microsoft Office Suite applications PowerPoint, Word, Excel and Outlook
- Strong analytical skills
- Excellent verbal, listening and written communication skills
- Ability to multitask and prioritize projects to meet scheduled deadlines and tight turnaround times
- Knowledge of US healthcare data, preferably in data operations role, is a plus
- Knowledge of data governance principles, data quality, and data lifecycle management a plus
- Experience with project management tools like JIRA
- Flexible work schedule
- Quick Learner, energetic and flexible