Total 4 job vacancies by IntegriChain

Join our DevOps Engineering team as a Senior Database Engineer to design, build, and engineer cloud-native database platforms across a modern, multi-engine data stack. This is an engineering role, not a DBA role, focused on building scalable systems, writing infrastructure-as-code, and embedding databases into software delivery pipelines.

You'll work closely with DevOps and Product Engineering to build high-performing data infrastructure that supports critical applications and analytics.  You will own and evolve a diverse ecosystem spanning AWS RDS, Aurora, DynamoDB, Redshift, Azure SQL, PostgreSQL, Snowflake, and NoSQL engines, integrating AI-driven automation and MLOps-ready data foundations to support critical applications and machine learning workflows.

Key Responsibilities

Multi-Engine Cloud Data Architecture & Platform Engineering

• Design, build, and engineer hybrid data solutions spanning relational (PostgreSQL, Aurora, RDS, Azure SQL), columnar (Redshift, Snowflake), and NoSQL (DynamoDB, DocumentDB, OpenSearch) engines — selecting the right engine per workload.
• Architect cloud-native data lakehouse platforms on AWS using S3, Lake Formation, Glue, and open formats (Apache Iceberg, Delta Lake, Parquet), with Azure Data Lake as a secondary target.
• Implement and manage Medallion Architecture (Bronze / Silver / Gold) patterns to support raw ingestion, curated analytics, and business-ready datasets.
• Build and optimize hybrid data platforms spanning operational databases (PostgreSQL / RDS / Aurora / DynamoDB) and analytical systems (Snowflake / Redshift).
• Develop and maintain semantic layers and analytics models to enable consistent, reusable metrics across BI, analytics, and AI use cases.
• Engineer efficient data models, ETL/ELT pipelines, and query performance tuning for analytical and transactional workloads.
• Engineer replication topologies, partitioning strategies, and data lifecycle automation as code — not manual DBA operations.
• 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.

Advanced Data Pipelines, Streaming & Orchestration

• Engineer ELT/ETL pipelines using AWS-native services (Glue, Kinesis, MSK, Step Functions, EventBridge) and modern tooling (dbt, Airflow) for batch, micro-batch, and near-real-time workloads.
• 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.
• Architect DocumentDB (MongoDB-compatible) clusters for document workloads requiring flexible schema and hierarchical data models.
• Build and manage OpenSearch / ElasticSearch clusters for full-text search, log analytics, and observability use cases.
• Evaluate and recommend the right NoSQL engine (DynamoDB vs DocumentDB vs OpenSearch vs ElastiCache) based on access patterns, latency, and cost profile.
• Implement TTL policies, DynamoDB Accelerator (DAX), and ElastiCache (Redis/Memcached) for high-throughput caching layers.

AI-Enabled Data Engineering & MLOps Foundations

• Apply AI and ML techniques to data architecture and operations, including intelligent data quality validation, anomaly detection, schema drift detection, and query workload pattern analysis — using AWS SageMaker and Amazon Bedrock.
• Design and build ML-ready data foundations: SageMaker Feature Store, training dataset pipelines, experiment tracking, and inference data pipelines using AWS-native MLOps services.
• Integrate LLM capabilities via Amazon Bedrock for AI-assisted data documentation, query generation, lineage summarization, and automated data cataloging.
• Implement vector database solutions (pgvector on Aurora/RDS, OpenSearch k-NN) to support AI similarity search and retrieval-augmented generation (RAG) use cases.
• Build AI-powered observability using ML-driven anomaly detection on pipeline metrics, query performance trends, and data quality SLAs.

Software Engineering, DevOps & Infrastructure as Code

• Build and manage all data infrastructure as code using Terraform and AWS CDK — covering RDS, Aurora, DynamoDB, Redshift, Glue, MSK, Kinesis, Snowflake, and supporting IAM/networking components.
• Integrate database changes into CI/CD pipelines (GitHub Actions, AWS CodePipeline) with automated schema testing, data contract validation, deployment, and rollback.
• Develop internal platform tooling using Python, SQL, and AWS SDK (boto3) — building self-service capabilities that allow engineers to provision governed database environments on demand.
• Implement database-as-code practices: automated schema migrations, snapshot/restore testing pipelines, and environment clone automation — eliminating manual DBA provisioning tasks.
• Build and publish internal data platform APIs and SDKs that abstract database complexity from application teams.

Security, Governance & Compliance Engineering

• Engineer enterprise-grade data governance across all engines: RBAC, column/row-level security, field-level encryption, dynamic data masking, and comprehensive audit logging, implemented as code, not manual configuration.
• Define and enforce data contracts and ownership using AWS Lake Formation, Glue Data Catalog, and Snowflake governance — versioned and managed in source control.
• Partner with Security and Compliance teams to ensure audit readiness and regulatory alignment (SOC 2, HIPAA, GDPR where applicable).
• Manage AWS IAM policies, KMS encryption, VPC security groups, and private endpoints (PrivateLink, VPC Endpoints) for least-privilege access and network isolation.
• Implement secrets management using AWS Secrets Manager and Parameter Store with automated credential rotation for all database engines.

Job Profile

• Process Chargeback claims and Resubmissions: The Chargeback analyst analyzes and validates all chargeback lines for assigned customer accounts. The Chargeback analyst is responsible for identifying root cause of issues with discrepancies and takes corrective action to eliminate future occurrences and reduce outstanding wholesaler chargeback deduction balance.
• The Chargeback analyst is responsible for researching chargeback rejections due to invalid data. The incumbent works with wholesalers and internal contract/membership groups to resolve issues for problematic chargebacks including errors associated with pricing, membership, eligibility, dating and claims data.
• The chargeback analyst will also perform ad hoc reports and projects as required. Performs Daily and Monthly Reconciliations
• The Chargeback analyst will perform a daily and monthly reconciliation of inbound chargebacks to the EDI 844 transmission to ensure completeness. The Chargeback analyst also performs a daily reconciliation of outbound chargebacks to the EDI 849 transmission.
• Interact with Internal and External Customers: The Chargeback analyst responds to wholesaler inquiries. as well as works with the Contracted Entities to resolve pricing or membership questions and discrepancies. The analyst also works cross functionally as required to research and resolve issues.

Your mission at IntegriChain:

To help ensure success of high quality and on time delivery of rebate claims processing for IntegriChain’s Managed Services Customers.

What this role entails:  

• Process Managed Care Rebates
• Download, log and track rebate and contract submissions
• Run and create reports/analysis in Excel spreadsheets and other software packages to support payment reviews and approvals
• Ensure rebate calculations are in compliance with contractual terms
• Reconcile and document any rebate variances
• Resolve errors and disputes within the rebate system based on defined set of rules and procedures
• Follow and ensure compliance with defined business processes and pre-established guidelines to perform analyst functions
• Provide updates to team leads/management as required on delivery status of assigned tasks
• Ensure department SLA’s and quality expectations are met
• Prepare and analyze ad hoc reporting
• Support ad hoc projects

What success looks like in this role:

• Rebate claims are delivered on time and are of high quality
• Data and contracts are downloaded within required SLAs
• Compliance with department business processes
• Proactive and clear communication with Team Lead and other business partners

To help ensure success of high quality and on time delivery of rebate claims processing for IntegriChain’s Managed Services Customers.

What this role entails:  

• Process and analyze rebate claims within multiple business areas per the business area SLAs
• Ensure that all business area SLAs and quality expectations are met
• Escalate all business areas issues accordingly and resolve appropriately
• Oversight of 6-8 analyst level resources
• Maintain and enhance the team’s knowledge within the business areas detailed responsibilities
• Understand and ensure team’s compliance of company and departments business processes and policies
• Assist analysts with validation and troubleshooting system issues
• Support onboarding and training of team members
• Provide status updates, reporting and analysis as required
• Support system testing
• Support ad hoc projects

What success looks like in this role:

• Rebate claims are delivered on time and are of high quality
• Team is engaged in their roles and department success
• Compliance with department business processes
• Strong communication with direct manager on both accomplishments and challenges within team
• Partner with other team leads to support department processes and policies