Data Engineer (hybrid)

Data Engineer (Hybrid)

We are seeking a skilled Data Engineer to design, develop, and optimize scalable data pipelines and data platforms that support enterprise analytics, reporting, AI/ML initiatives, and healthcare business operations.

The ideal candidate will have strong expertise in cloud-based data engineering, ETL/ELT development, big data technologies, and data quality practices, with experience working in healthcare environments. Key Responsibilities:

• Design, develop, and maintain scalable ETL/ELT pipelines for structured and unstructured data.
• Build and optimize data ingestion frameworks from multiple source systems, APIs, databases, and cloud platforms.
• Develop and maintain enterprise data models, data warehouses, and data lakes.
• Ensure high levels of data quality, integrity, security, and governance across data platforms.
• Collaborate with business analysts, architects, data scientists, and application teams to understand data requirements.
• Implement data transformation, validation, reconciliation, and monitoring processes.
• Optimize performance of large-scale data pipelines and database workloads.
• Support analytics, reporting, AI/ML, and advanced data science initiatives through reliable data delivery.
• Implement metadata management, lineage tracking, and data cataloging solutions.
• Troubleshoot production issues and perform root cause analysis for data-related incidents.
• Participate in code reviews, architecture discussions, and technical design sessions.
• Ensure adherence to healthcare regulatory and compliance requirements, including HIPAA and data privacy standards.
• Work with distributed teams across multiple locations and support enterprise-scale data initiatives.

Required Skills:

• Data Engineering
• Data Pipeline Development
• ETL/ELT Design and Development
• Data Warehousing Concepts
• Data Modeling (Dimensional & Relational)
• Data Lake Architecture
• Data Quality and Data Governance
• Cloud Technologies
• AWS (Glue, EMR, Lambda, S3, Redshift, Athena) or Azure (ADF, Data Lake, Synapse, Databricks)
• Databases
• SQL Server
• Oracle
• PostgreSQL
• Snowflake
• Programming
• Python
• SQL
• PySpark
• Shell Scripting
• Big Data Technologies
• Apache Spark
• Hadoop Ecosystem
• Kafka (Preferred)
• DevOps & CI/CD
• Git
• Jenkins/Azure DevOps CI/CD Pipeline Implementation

Preferred Qualifications:

• Experience in Healthcare, Health Insurance, or Life Sciences domain.
• Exposure to AI/ML data pipelines and MLOps frameworks.
• Knowledge of healthcare data standards such as HL7, FHIR, ICD, and CPT is preferred.
• Experience with Snowflake, Databricks, or modern cloud-native data platforms.
• Familiarity with Agile/Scrum methodology.

Education:

• Bachelor's or Master's degree in Computer Science, Information Technology, Data Engineering, or related field.

Key Competencies:

• Strong analytical and problem-solving skills.
• Excellent communication and stakeholder management abilities.
• Ability to work independently in fast-paced environments.
• Strong collaboration and mentoring capabilities.
• Commitment to quality, scalability, and continuous improvement.