In Person interview for Sr Data Engineer @ Oklahoma City, OK---Must be loca

Saxon Global•Oklahoma City, OK

5d•Onsite

About The Position

This position is responsible for the design, development, and management of data pipelines, integration workflows, data migration, and data transformation. The role will also manage the analytical infrastructure that supports organizational activities, ensuring data flows reliably and securely in compliance with all relevant regulations and data governance requirements.

Requirements

A minimum of five (5) years of hands-on data engineering experience is required.
Expert-level proficiency in SQL, including correlated subqueries and window functions.
Proficiency in Python for data pipeline development, automation, and API integration, including libraries like pandas, numpy, and SQLAlchemy.
Experience with ETL/transformation tools such as Azure Data Factory, GCP Dataproc and Dataflow, SSIS, or dbt.
Experience with orchestration tools.
Experience consuming and integrating REST APIs for data ingestion and system interoperability.
Proficiency with version control systems, such as Git.
Familiarity with R for statistical analysis and data manipulation.
Familiarity with Python machine learning libraries.
Strong written and verbal communication skills.
Ability to manage multiple priorities and deadlines effectively.
Capability to exercise sound judgment and maintain confidentiality when handling sensitive information.
Skill in fostering a collaborative and inclusive work environment.

Nice To Haves

A Bachelor's degree in Computer Science, Engineering, Data Engineering, or a related field.
Experience in a HIPAA-regulated environment with demonstrated knowledge of data privacy and security requirements.
Experience with standards-based health data exchange (HL7 v2/v3, FHIR).
Experience applying cell suppression and statistical disclosure logic within SQL.
Familiarity with SAS.

Responsibilities

Design, implement, and maintain ELT/ETL pipelines across cloud platforms such as Azure, GCP, and AWS.
Architect and modernize robust data acquisition and ingestion pipelines for large-scale healthcare data.
Implement and manage data storage solutions, including data lakes and warehouses, utilizing appropriate partitioning, security, and lifecycle policies.
Plan and execute data migrations across platforms and systems, ensuring data integrity and compliance.
Design schemas to support the migration of transactional database structures to data warehouse environments.
Evaluate and integrate new data sources and develop processes to support novel data types.
Translate business needs into technical solutions within an agile environment.
Collaborate with internal teams to define data models and Service Level Agreements (SLAs).
Provide technical guidance and mentorship to team members.
Document data architectures, data lineage, and standards.