Senior Software Systems Engineer
Integrated Resources Inc
Job Title: Senior Software Systems Engineer
Job Location: Richmond, VA
Job Duration: 11-12 Months (possibility of extension)
Job Summary:
Job Location: Richmond, VA
Job Duration: 11-12 Months (possibility of extension)
Job Summary:
- The IT Architect - Data & Snowflake is a strategic technical leader within the Enterprise Data & Analytics team, responsible for defining the architecture, standards, best practices and future direction of the enterprise data platform.
- This role designs scalable data pipelines, governs Snowflake usage across the organization, and develops high quality data models that power analytics, BI, AI/ML, and data driven decision making.
- The architect ensures that the data ecosystem is secure, governed, cost optimized, and capable of supporting enterprise self service analytics, operational reporting, and advanced analytics initiatives.
- We are seeking a hands on Data Architect with a strong ETL and Data Engineering background to design, build, and optimize large scale data ingestion, transformation, and delivery platforms.
- This role is focused on creating reliable, observable, and high performance data pipelines that support enterprise analytics, reporting, and advanced AI/ML use cases.
- You will architect end to end data engineering solutions across on prem and cloud platforms, lead data integration strategy, and establish best practices around data quality, monitoring, and operational excellence.
- Serve as the technical authority for ETL and data engineering architecture.
- Review pipeline designs, code standards, and performance benchmarks.
- Mentor and guide data engineers on best practices and modern data engineering patterns.
- Partner with stakeholders to translate business data requirements into scalable technical solutions.
- Ability to lead complex data engineering initiatives in enterprise environments.
- Design and own end to end ETL/ELT architectures for batch and incremental data processing.
- Define patterns for data ingestion from Oracle Exadata and other source systems into cloud platforms.
- Architect high volume, high throughput pipelines supporting structured and semi structured data.
- Continuously evaluate and improve data infrastructure and workflows.
- Data transformation logic.
- Schema evolution.
- Error handling and reprocessing.
- Performance tuning.
- Metadata management.
- Parameterization and reusability.
- Pipeline deployment and versioning.
- Batch and incremental data processing.
- ELT patterns and push down processing.
- Performance tuning of large ETL workloads.
- Architect end to end data pipelines (batch, streaming, real time) to support enterprise analytics, BI, and data products.
- Define architectural standards, including database design, warehouse sizing, multi-cluster strategies, RBAC, and performance optimization.
- Create and maintain enterprise semantic models, curated datasets, and reusable data assets to enable self-service analytics.
- Develop architecture patterns for AI/ML feature pipelines, analytical sandboxes, and model scoring in Snowflake.
- Establish data engineering, modeling, and transformation standards across the analytics ecosystem (e.g., naming conventions, ELT frameworks, versioning).
- Implement DevOps/Data Ops practices-CI/CD pipelines, automated testing, data quality checks, and observability across data pipelines.
- Partner with Data Governance to define standards for data quality, lineage, metadata management, and cataloging.
- Implement Snowflake security, access controls, auditing, and cost management practices.
- Collaborate with BI and analytics teams to design scalable, governed data models supporting dashboards, KPIs, and advanced analytics.
- Architect data solutions that support predictive analytics, forecasting, segmentation, and personalization use cases.
- Guide development of data products, ensuring they follow enterprise standards and meet business requirements.
- Partner with data engineering, analytics, business SMEs, cloud infrastructure, and cybersecurity teams to design reliable and secure data architectures.
- Translate business needs into scalable technical solutions that support enterprise reporting, analytics, and insight generation.
- Participate in Architecture Review Boards, solution design sessions, and enterprise data strategy planning.
- Establish standards for monitoring, alerting, SLA/SLO management, and operational resiliency of analytics pipelines.
- Ensure data solutions meet enterprise requirements for reliability, performance, scalability, and disaster recovery.
- Lead root cause analysis for data platform issues and drive remediation of architectural gaps.
- Proven experience with data quality, data observability, and pipeline monitoring.
- Minimum of a High School Diploma or Equivalency.
- 7+ years in data architecture, data engineering, or enterprise data platform roles.
- MUST have a minimum of 7+ years in data architecture, data engineering, or enterprise data platform roles.
- MUST have hands on advanced experience with Snowflake, Oracle Exadata, including performance tuning, RBAC, resource management, and advanced Snowflake features (streams, tasks, data sharing).
- MUST have strong proficiency with SQL, ELT/ETL frameworks, and cloud data services (Azure/AWS).
- Must have expertise designing analytical data models (Star/Snowflake schemas, data vault, semantic layers.
- Experience building scalable data pipelines using tools like dbt, Airflow, ADF, Databricks, Informatica, Talend or similar.
- Experience with Dataiku for analytics and ML pipeline enablement.
- Strong communication skills both verbal and written.
- Ability to lead, collaborate, or work effectively in a variety of teams, including multi-disciplinary teams.
- Cloud or platform certifications (Snowflake, Databricks, Azure, Informatica).
- Teams - Camera On.
Vacancy posted 20 hours ago
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