Job Description

Roles & Responsibilities

As a Data Engineer at Innovaccer, you will be at the heart of our data infrastructure designing, building, and maintaining the scalable pipelines and platforms that power our AI-driven healthcare solutions across the Kingdom of Saudi Arabia. You will play a key role in enabling data-driven decision-making for health systems, payers, and providers, directly contributing to better patient outcomes and operational excellence across the Saudi healthcare landscape.

A Day in the Life

• Design, develop, and maintain robust ETL/ELT data pipelines to ingest, transform, and deliver healthcare data from multiple source systems.
• Build and optimize scalable data models within cloud data warehouses (Snowflake, AWS Redshift, or Azure Synapse) to support analytics and reporting.
• Collaborate with data scientists, product managers, and clinical informatics teams to understand data needs and translate them into reliable data solutions.
• Ensure data quality, integrity, and governance by implementing testing frameworks, validation checks, and monitoring alerts across all pipelines.
• Work with healthcare interoperability standards (HL7, FHIR) to integrate clinical and claims data from diverse health systems in the KSA market.
• Contribute to infrastructure-as-code practices, supporting CI/CD pipelines and automating deployment of data workflows.
• Participate in code reviews, architectural discussions, and cross-functional sprint planning to ensure delivery of high-quality, production-grade data products.

Desired Candidate Profile

• Strong understanding of data engineering principles including data modelling, warehousing, and pipeline architecture.
• Familiarity with healthcare data standards such as HL7, FHIR, ICD-10, and SNOMED CT.
• Knowledge of cloud platforms (AWS, Azure, or GCP) and their managed data services.
• Ability to write clean, efficient, and well-documented code in Python and SQL.
• Ability to independently own and deliver data pipeline projects end-to-end, from requirements gathering to production deployment.
• Ability to troubleshoot complex data issues and communicate findings clearly to both technical and non-technical stakeholders.
• 3 – 6 years of hands-on experience in data engineering or a closely related role.
• Bachelor's or Master's degree in Computer Science, Information Systems, Engineering, or a related field.
• Proven experience with distributed processing frameworks such as Apache Spark or Kafka.
• Experience with orchestration tools (Apache Airflow, Prefect, or similar) to manage complex workflow dependencies.
• Prior experience working in healthcare IT or with clinical/claims datasets is strongly preferred.
• Proficiency in dbt (data build tool) for analytics engineering and data transformation workflows.
• Experience with real-time streaming pipelines using Apache Kafka or AWS Kinesis.
• Familiarity with data observability and monitoring tools such as Monte Carlo, Great Expectations, or similar.
• Understanding of HIPAA, PDPL (Saudi Personal Data Protection Law), and data privacy best practices in a healthcare context.
• Experience working in an Agile/Scrum environment with cross-functional global teams.
• Knowledge of Arabic language is a plus for stakeholder communication within the KSA market.