Sutherland is seeking a reliable and technical person to join us as GCP Data Engineer who will play a key role in driving our continued product growth and innovation. If you are looking to build a fulfilling career and are confident you have the skills and experience to help us succeed, we want to work with you!!

Key Responsibilities:

• Design and implement real-time data ingestion pipelines using Pub/Sub and Kafka Streams for healthcare data formats (HL7, FHIR)
• Build a robust Bronze layer as the single source of truth, storing raw, untransformed data in Cloud Storage
• Develop streaming ingestion patterns using Dataflow for real-time data capture with minimal transformation
• Implement batch loading processes using Dataproc for large-volume data from diverse sources (logs, databases, APIs)
• Apply schema inference and basic data type adjustments while preserving raw data lineage
• Design partitioning strategies in Cloud Storage for efficient historical data archival and retrieval
• Establish data landing zone controls including audit logging, versioning, and immutability patterns
• Create automated workflows using Cloud Composer for orchestrating ingestion pipelines
• Implement data catalog and metadata management for raw data assets

Required Skills:

• 5+ years of experience with GCP services (Cloud Storage, Pub/Sub, Dataflow, Dataproc, Cloud Composer)
• Strong expertise in Apache Kafka, Kafka Streams, and event-driven architectures
• Proficiency in Python and/or Java for data pipeline development using Apache Beam SDK
• Experience with healthcare data standards (HL7, FHIR) and handling semi-structured data
• Hands-on experience with streaming frameworks (Apache Beam, Dataflow) for near-real-time ingestion
• Knowledge of file formats and compression (JSON, Avro, Parquet) for raw data storage
• Understanding of CDC patterns, incremental loading, and data versioning strategies
• Experience with Cloud Storage lifecycle management and cost optimization

Preferred Qualifications:

• GCP Professional Data Engineer certification
• Experience with Confluent Platform or Google Cloud managed Kafka (if applicable)
• Familiarity with healthcare compliance requirements (HIPAA) and data residency
• Background in log aggregation platforms (Fluentd, Logstash) and observability
• Knowledge of data lake security patterns and IAM controls

Preferred Qualifications:

• GCP Professional Data Engineer certification
• Experience with Confluent Platform or Google Cloud managed Kafka (if applicable)
• Familiarity with healthcare compliance requirements (HIPAA) and data residency
• Background in log aggregation platforms (Fluentd, Logstash) and observability
• Knowledge of data lake security patterns and IAM controls