Data Engineer
About The Position
We are seeking a skilled Data Engineer with strong expertise in cloud-based data engineering, ETL/ELT development, and big data technologies. The ideal candidate will have experience working in healthcare environments and possess proficiency in major cloud platforms like AWS or Azure. This role involves designing, developing, and maintaining scalable data pipelines, data models, and data warehouses/lakes, ensuring high data quality and governance. You will collaborate with various teams to meet data requirements and support analytics, reporting, and advanced data science initiatives. The position requires strong programming skills in Python, SQL, and PySpark, along with knowledge of Big Data technologies and DevOps practices. Experience with healthcare data standards and regulatory compliance (HIPAA) is crucial.
Requirements
- Strong expertise in cloud-based data engineering, ETL/ELT development, and big data technologies.
- Experience working in healthcare environments.
- Proficiency in AWS (Glue, EMR, Lambda, S3, Redshift, Athena) or Azure (ADF, Data Lake, Synapse, Databricks).
- Experience with databases such as SQL Server, Oracle, PostgreSQL, or Snowflake.
- Strong programming skills in Python, SQL, PySpark, and Shell Scripting.
- Knowledge of Big Data Technologies including Apache Spark and Hadoop Ecosystem.
- Experience with DevOps and CI/CD tools like Git and Jenkins/Azure DevOps.
- Familiarity with Agile/Scrum methodology.
- Strong analytical and problem-solving skills.
- Excellent communication and presentation skills.
- Ability to communicate effectively with stakeholders.
- Ability to work independently in fast-paced environments.
- Strong collaboration and mentoring capabilities.
Nice To Haves
- Knowledge of healthcare data standards such as HL7, FHIR, ICD, and CPT.
- Experience in Healthcare, Health Insurance, or Life Sciences domain.
- Exposure to AI/ML data pipelines and MLOps frameworks.
- Experience with Kafka.
- Experience with Snowflake, Databricks, or modern cloud-native data platforms.
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.
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
