Data Architect

About this Position:

Job Title: Data Architect

Qualifications and experience:

• A minimum of a Bachelor's (4-year) degree in Computer Science, Analytics/Data Science, Information Systems, Business Administration, Public Health Informatics, or another related field.

• Current data and/or analytics certification such as Certified Data Management Professional (CDMP). Eighteen or more hours of participation in webinars or conferences over the last 3 years related to data and analytics may be substituted for the certification.

• A minimum of five or more years of experience interfacing directly with various lines of business; must demonstrate an understanding of general business operations, preferably related to healthcare, and be able to articulate technical architectures, solutions, and data models to a non-technical audience.

• A minimum six or more years of experience architecting, engineering, implementing, and supporting data warehouses including two or more years of experience with Snowflake Data Warehouse.

• A minimum of three or more years of experience architecting, engineering, implementing, and supporting cloud-based data lakes, including lake layers and bucket structures in AWS S3 and related Apache Foundation tools such as Parquet.

• A minimum of two or more years of experience architecting, engineering, implementing, and supporting cloud data lakehouse structures and tools such as Databricks, Snowflake, AWS, or open-source technology such as Delta Lake, Hudi, and Iceberg.

• A minimum of ten or more years of experience in data modeling (including Entity Relationship, Logical, Conceptual, and Physical models), and data profiling/reverse engineering in both schema-on-read and schema-on-write environments. The experience must include proficiency with erwin data modeler.

• A minimum of six or more years of experience with data pipeline/Integration tools, including deployment, mapping/design, observability, orchestration, performance optimization, testing, and engineering, via various methods (i.e., ETL/batch, CDC, Streaming) using tools such as Informatica, AWS Glue, MuleSoft, Spark, AWS Kinesis, or Kafka.

• A minimum of six or more years of experience with SQL programming, three or more years of experience with Python or a similar object-oriented high-level programming language and one or more years of experience with AWS Lambda functions.

• A minimum of five or more years of experience architecting and engineering relational (both row and columnar) and NoSQL (i.e., Document, Graph, Vector, Key-Value) databases.

• A minimum of three or more years of experience working with cloud infrastructure and security teams to design and implement an AWS cloud infrastructure that hosts a data and analytics ecosystem.

• A minimum of three or more years of experience working with security teams to architect and engineer data protection, data loss prevention, user role and attribute-based access controls (RBAC or ABAC), and privacy compliance (with an emphasis on HIPAA) within a cloud data and analytics ecosystem.

• A minimum of three or more years of experience designing and implementing internal and external data sharing hubs as well as incorporating the use of, governing, and optimizing APIs for data exchanges.

• A minimum of two or more years of experience utilizing Dev or DataOps processes.

• A minimum of five or more years of data and analytics testing/quality assurance and acceptance experience, including best practices, tools, and automation.

• A minimum of three or more years of experience architecting, engineering, implementing, and supporting the following data governance/management solutions: Data Quality, Data Catalog and/or Metadata Management, and Data Profiling/Lineage in tools such as Informatica IDMC, Collibra, or Precisely.

• A minimum of two or more years of experience architecting, engineering, implementing, and supporting a Master Data Management (MDM) solution using tools such as Informatica MDM, Semarchy, or Reltio.

• A minimum of four or more years of experience architecting and implementing cloud-based Analytics & Business Intelligence (ABI) tools such as Qlik, Tableau or PowerBI.

• A minimum of two or more years of experience architecting and implementing cloud-based Data Science and Machine Learning platforms (DSML) such as SAS Viya, AWS Sagemaker, or Dataiku, including statistical model life-cycle management, endpoints, and machine learning.