Data Engineer
6 days ago
Data Engineer
Key Responsibilities :
- Design and implement enterprise-grade data warehouse solutions, including developing dimensional and normalized data models from scratch to support reporting, analytics, and machine learning use cases
- Build and maintain star and snowflake schemas, slowly changing dimensions (SCD), and other data modeling patterns aligned with business logic
- Own end-to-end data architecture design, including schema evolution, data quality frameworks, and comprehensive documentation for data models
- Collaborate with analytics and product teams to translate business metrics into data warehouse structures and KPIs
- Design and implement scalable ETL/ELT pipelines for processing large-scale structured and unstructured healthcare datasets across multiple sources
- Build robust data ingestion frameworks to handle real-time and batch data processing from various healthcare systems, IoT devices, and third-party APIs
- Develop and maintain data quality monitoring and validation systems to ensure data integrity and accuracy across the data warehouse
- Implement data governance practices including data lineage tracking, metadata management, and access controls
- Build automated data testing and monitoring pipelines to detect anomalies and ensure SLA compliance
- Collaborate with ML engineers to create feature stores and data pipelines that support machine learning model development and deployment
Required Skills and Experience:
years of experience in data engineering with a strong focus on data warehouse design and implementation
- Proficiency in SQL and database technologies (PostgreSQL, MySQL, Snowflake, BigQuery, Redshift)
- Expert-level experience with data processing frameworks including Apache Spark, PySpark, and distributed computing concepts
- Hands-on experience with ETL/ELT tools and frameworks (Apache Airflow, dbt, Fivetran, or similar)
- Strong experience with cloud data platforms (AWS Data Services, GCP BigQuery/Dataflow, or Azure Data Factory)
- Proficiency in Python and/or Scala for data pipeline development and automation
- Experience with data modeling techniques including dimensional modeling, data vault, and normalization strategies
- Understanding of data governance, security, and compliance requirements, especially in healthcare contexts
Preferred Qualifications :
- Bachelor's degree in Computer Science, Data Engineering, Information Systems, or related technical discipline
- Experience with real-time data processing using technologies like Apache Kafka, Kinesis, or Pub/Sub
- Exposure to HealthTech or Healthcare services domain with understanding of healthcare data standards (HL7, FHIR)
- Experience with data lake architectures and modern data stack implementations
- Familiarity with Infrastructure as Code (Terraform, CloudFormation) for data infrastructure management
- Knowledge of containerization technologies (Docker, Kubernetes) for data pipeline deployment
Duration: 3-6 Months contract role
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