Data Pipelines & Analytics Engineer

PDS Health; Irvine (CA); On-site; USD 93,000 - 117,000; Full time

Benefits offered by this job

Medical, dental, and vision insurance

Paid time off

Tuition Reimbursement

401K

Paid volunteer time

Job summary

PDS Health is seeking an Engineer, Data Management and Analytics to support data solutions, analysis, and reporting. You will apply system analysis techniques to determine hardware, software, and system specifications and collaborate across stakeholders to deliver scalable data flows.

Responsibilities include building and optimizing data pipelines, validating data quality, and supporting data infrastructure such as data warehouses and data lakes.

Qualifications

• Bachelor’s degree or 5+ years of experience in related field.
• 2+ years of experience in database development, OLTP, Data Warehouse/Dimensional modeling, cloud data platforms, pipelines, agile, and source control.
• Proficiency in SQL, Python, and Scala.

Responsibilities

• Collaborate with Data Warehouse Product Owner and Business System Analyst to understand business needs and write user stories.
• Work with Sr Engineer and Data Architect to develop data flows and pipelines.
• Build data pipeline flow to load data from various sources and apply complex business logic to normalized/denormalized structures.
• Diagnose and fix data pipelines, data quality, and accessibility issues.
• Manage and optimize data warehouse, data lake, and other data infrastructure components.
• Develop and implement data validation rules, monitor systems, and maintain data lineage for accuracy and reliability.
• Implement automation to streamline data workflows and reduce manual effort.
• Other duties as assigned.

Skills

SQL

Python

Scala

Education

Bachelor’s degree in Computer Science, MIS, or related field

Tools

SSIS

Microsoft Fabric

Airflow

Dagster

Kafka

Job description

PDS Health is seeking an Engineer, Data Management and Analytics to support data solutions, analysis, and reporting. You will apply system analysis techniques to determine hardware, software, and system specifications and collaborate across stakeholders to deliver scalable data flows.

Responsibilities include building and optimizing data pipelines, validating data quality, and supporting data infrastructure such as data warehouses and data lakes.