Data Architect

Pharma Logistics•Libertyville, IL

10d•$170,000 - $190,000•Onsite

About The Position

The Data Architect owns the organization's data foundation and is responsible for designing data models, building and maintaining ETL/ELT pipelines that integrate operational data into Snowflake, and ensuring enterprise data performance, quality, and security. The role delivers trusted, well-modeled data for reporting, self-service analytics, and data science. The Data Architect designs and maintains enterprise data architecture and conceptual, logical, and physical data models. The role builds, monitors, and supports pipelines integrating data from SQL Server, NoSQL databases, and cloud SaaS applications into Snowflake; establishes data quality, governance, documentation, and security practices; and diagnoses performance and cost issues. The position collaborates with report writers, data scientists, business analysts, architects, and developers, evaluates data technologies, and handles data-related help desk cases and other projects.

Requirements

Minimum of 7 years of experience in data engineering, database development, or data architecture.
Understanding of Pharma Logistics services, processes, and systems, or ability to learn them quickly.
Proven experience designing dimensional, relational, and NoSQL document data models.
Hands-on experience with Snowflake, including data loading, modeling, performance tuning, and cost management.
Strong experience with MS SQL Server development and administration.
Experience with NoSQL document databases such as Azure Cosmos DB and Couchbase/CouchDB.
Demonstrated experience building and supporting production ETL/ELT pipelines.
Experience integrating data from cloud SaaS applications through APIs and connectors.
Strong ability to diagnose and resolve performance issues across databases and pipelines.
Advanced SQL/T-SQL skills.
Knowledge of Snowflake Snowpipe, streams, tasks, roles, and warehouses.
Knowledge of MS SQL Server SSIS and query optimization.
Knowledge of ETL/ELT tools such as Fivetran, Matillion, Azure Data Factory, or Airbyte.
Knowledge of dbt, Python, REST APIs, and JSON.
Ability to prioritize multiple projects with varying deadlines.
Ability to work independently and as part of a team.
Self-starter who can work in a fast-paced environment.
Accuracy and attention to detail.

Nice To Haves

Bachelor's degree in Computer Science, Information Systems, Data Engineering, or a related field.
Snowflake SnowPro or Microsoft Azure data certification.
Experience leading a migration from legacy reporting databases to a cloud data warehouse.
Experience with data governance frameworks and master data management.
Knowledge of pharmaceutical, reverse distribution, or logistics industry data and regulatory requirements.
Git/version control and CI/CD for data pipelines.

Responsibilities

Design and maintain enterprise data architecture, including data flows between operational systems, Snowflake, and downstream consumers.
Design conceptual, logical, and physical data models, including Snowflake dimensional models for reporting and analytics.
Build, maintain, and monitor ETL/ELT pipelines integrating MS SQL Server, Azure Cosmos DB, Couchbase/CouchDB, and cloud SaaS applications into Snowflake.
Identify and resolve database and pipeline performance issues, including query tuning, indexing, Snowflake warehouse sizing, and cost optimization.
Establish data quality checks, monitoring, and alerting to ensure data is accurate, complete, and timely.
Define and enforce data standards, naming conventions, and documentation, including a data dictionary and data lineage.
Implement data security and access controls, including role-based access and data masking, to protect sensitive and regulated data.
Partner with the Report Writer to deliver curated, certified datasets for Sigma reporting and self-service dashboards.
Partner with the Data Scientist to provide clean, well-structured data for analysis and modeling.
Work with Business Analysts, architects, and developers to define data requirements for new projects and system changes.
Evaluate and recommend data tools, platforms, and integration approaches.
Resolve help desk cases related to data, integrations, and pipelines.
Complete other ad hoc projects and reports.