The Senior Data Engineer leads and implements best-in-class data management strategies and practices through various forms of integration, data acquisition/ingestion, data cleansing/refinements, data transformations/conversions, data migrations, data purging, and back-ups. The incumbent works with a variety of users and stakeholders to understand data requirements and supports the data architecture to translate into the data management practice at Healthfirst. The Sr. Data Engineer authors artifacts defining standards and definitions for storing, processing, and moving data including associated processes and business rules. Additionally, the Sr. Data Engineer maps the details within these artifacts to business processes, non-functional characteristics, qualitative criteria, and technical enablement. He/she must constantly think through the needs of the business to support efficient and error-free processes. The Sr. Data Engineer finds trends in datasets and develops workflows and algorithms to highlight strategic raw data as useful to the enterprise. The Sr. Data Engineer creates data acquisition strategy and develops dataset processes in a robust manner according to best practices of standardization.

MINIMUM QUALIFICATIONS:

• 8+ Years overall IT experience
• Enterprise experience in scripting languages primarily Python and Pyspark building enterprise frameworks
• Enterprise experience in data ingestion methodologies using different etl tools(Glue,DBT or any other)
• Enterprise experience in data warehousing concepts and big data technologies like EMR, Hadoop
• Enterprise experience in any cloud infrastructure like AWS,GCP,Azure
• Strong SQL expertise across different relational and NoSQL Databases.

PREFERRED QUALIFICATIONS:

• Strong knowledge of data security, encryption, and compliance standards.
• Hands-on experience with CI/CD pipelines and DevOps practices in a data engineering environment.
• Experience in API building
• Experience building stream platforms

DUTIES AND RESPONSIBILITIES:

• Designs and implements standardized data management procedures around data staging, data ingestion, data preparation, data provisioning, and data destruction (e.g., scripts, programs, automation, etc.)
• Ensures quality of technical solutions as data moves across multiple zones and environments
• Provides insight into the changing data environment, data processing, data storage and utilization requirements for the company, and offer suggestions for solutions
• Ensures managed analytic assets to support the company’s strategic goals by creating and verifying data acquisition requirements and strategy
• Develops, constructs, tests, and maintains architectures
• Aligns architecture with business requirements and uses programming language and tools
• Identifies ways to improve data reliability, efficiency, and quality
• Conducts research for industry and business questions
• Deploys sophisticated analytics programs, machine learning, and statistical methods to efficiently implement solutions
• Prepares data for predictive and prescriptive modeling and find hidden patterns using data
• Uses data to discover tasks that can be automated
• Creates data monitoring capabilities for each business process and works with data consumers on updates
• Aligns data architecture to the solution architecture; contributes to overall solution architecture
• Develops patterns for standardizing the environment technology stack
• Helps maintain the integrity and security of company data
• Additional duties as assigned or required