Integrichain1

Integrichain1

Senior Database Engineer - Platform Engineering

Philadelphia, PA, United States · Senior

Sponsorship not specifiedDetected 67 days ago
PythonGitSQLNoSQLPostgreSQLMySQLMongoDBRedisElasticsearchDynamoDBSnowflakeRedshiftVector DatabasesAWSAzureCloud PlatformsTerraformCI/CDGitHub ActionsDevOpsPlatform EngineeringKafkaMachine LearningPandas

About the role

  • IntegriChain is the data and application backbone for market access departments of Life Sciences manufacturers.
  • For more information, visit www.integrichain.com, or follow us on Twitter @ IntegriChain and LinkedIn.

Responsibilities

  • Implement and manage Medallion Architecture (Bronze / Silver / Gold) patterns to support raw ingestion, curated analytics, and business-ready datasets.
  • Develop and maintain semantic layers and analytics models to enable consistent, reusable metrics across BI, analytics, and AI use cases.
  • Build automated schema migration pipelines (Flyway/Liquibase) and data versioning workflows integrated into CI/CD replacing manual schema change management.
  • Design and implement API-first data access patterns, enabling engineering teams to interact with databases through well-defined, versioned interfaces rather than direct connection strings.
  • Build streaming data pipelines using AWS Kinesis Data Streams, Kinesis Firehose, and MSK (Managed Kafka) for event-driven, low-latency ingestion across multiple database targets.
  • Implement data quality checks, schema enforcement, lineage, and observability across pipelines.
  • Optimize performance, cost, and scalability across ingestion, transformation, and consumption layers.
  • Implement change data capture (CDC) using AWS DMS, Debezium, or native engine features to synchronize data across SQL, NoSQL, and analytical systems.
  • NoSQL & Document Store Engineering
  • Design and optimize DynamoDB schemas using single-table design patterns, GSIs, LSIs, and DynamoDB Streams for event-driven architectures.

Requirements

  • Proficiency with Python (boto3, SQLAlchemy, pandas) and SQL for data transformation, automation, and tooling.
  • Experience integrating database workflows into CI/CD pipelines using GitHub Actions, CodePipeline, or similar.
  • ICyte is the first and only platform that unites the financial, operational, and commercial data sets required to support therapy access in the era of specialty and precision medicine.

Nice to have

  • Working knowledge of AWS Redshift, Glue, Lake Formation, Kinesis, MSK, and EventBridge for pipeline and lakehouse architectures.
  • Familiarity with Azure SQL, Azure Data Factory, or Azure Synapse is a plus.
  • Awareness of vector databases and embedding-based retrieval (pgvector, OpenSearch k-NN) is a strong plus.
  • Proficiency with Terraform for database and cloud infrastructure as code
  • AWS CDK experience is a plus.

Benefits

  • Architect DocumentDB (MongoDB-compatible) clusters for document workloads requiring flexible schema and hierarchical data models.
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