Senior Database Engineer

IntegriChain • Philadelphia, PA

5h

About The Position

​​​​​​Join our DevOps Engineering team as a Senior Database Engineer responsible for designing, optimizing, and automating cloud database solutions across AWS RDS, Postgres, and Snowflake. This role focuses on performance engineering, data integration, and automation -- ensuring our data platforms are scalable, reliable, and efficient. You’ll work closely with DevOps and Product Engineering to build high-performing data infrastructure that supports critical applications and analytics.

Requirements

• 5+ years of experience in data engineering, database engineering, or data platform development in production environments.
• Strong hands-on experience with Snowflake, including performance tuning, security, and cost optimization.
• Deep expertise with PostgreSQL and AWS RDS in cloud-native architectures.
• Proven experience designing lakehouse or modern data warehouse architectures.
• Strong understanding of Medallion Architecture, semantic layers, and analytics engineering best practices.
• Experience building and operating advanced ELT pipelines using modern tooling (e.g., dbt, orchestration frameworks).
• Proficiency with SQL and Python for data transformation, automation, and tooling.
• Experience with Terraform and infrastructure-as-code for data platforms.
• Solid understanding of data governance, observability, and reliability engineering.

Nice To Haves

• Experience with dbt, AWS Glue, Airflow, or similar orchestration tools.
• Familiarity with feature stores, ML pipelines, or MLOps workflows.
• Exposure to data observability platforms and cost optimization strategies.
• Relevant certifications (Snowflake SnowPro, AWS Database Specialty, etc.).

Responsibilities

• Design, build, and optimize database solutions using Snowflake, PostgreSQL, and Oracle RDS.
• Design and evolve cloud-native data lakehouse architectures using Snowflake, AWS, and open data formats where appropriate.
• 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) and analytical systems (Snowflake).
• 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.
• Implement replication, partitioning, and data lifecycle management to enhance scalability and resilience.
• Manage schema evolution, data versioning, and change management in multienvironment deployments
• Engineer highly reliable ELT pipelines using modern tooling (e.g., dbt, cloud-native services, event-driven ingestion).
• Design pipelines that support batch, micro-batch, and near–real-time processing.
• Implement data quality checks, schema enforcement, lineage, and observability across pipelines.
• Optimize performance, cost, and scalability across ingestion, transformation, and consumption layers.
• Apply AI and ML techniques to data architecture and operations, including:
• Intelligent data quality validation and anomaly detection
• Automated schema drift detection and impact analysis
• Query optimization and workload pattern analysis
• Design data foundations that support ML feature stores, training datasets, and inference pipelines.
• Collaborate with Data Science teams to ensure data platforms are AI-ready, reproducible, and governed.
• Build and manage data infrastructure as code using Terraform and cloud-native services.
• Integrate data platforms into CI/CD pipelines, enabling automated testing, deployment, and rollback of data changes.
• Develop tooling and automation (Python, SQL, APIs) to streamline provisioning, monitoring, and operational workflows.
• Implement enterprise-grade data governance, including role-based access control, encryption, masking, and auditing.
• Enforce data contracts, ownership, and lifecycle management across the lakehouse.
• Partner with Security and Compliance teams to ensure audit readiness and regulatory alignment.
• Build and manage data infrastructure as code using Terraform and cloud-native services.
• Integrate data platforms into CI/CD pipelines, enabling automated testing, deployment, and rollback of data changes.
• Develop tooling and automation (Python, SQL, APIs) to streamline provisioning, monitoring, and operational workflows.

Benefits

• Excellent and affordable medical benefits + non-medical perks including Student Loan Reimbursement, Flexible Paid Time Off and Paid Parental Leave
• 401(k) Plan with a Company Match to prepare for your future
• Robust Learning & Development opportunities including over 700+ development courses free to all employees

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: No Education Listed
• Number of Employees: 501-1,000 employees