Senior Data Engineer

As a Senior Data Engineer , you will take a lead technical role on our core data platform: designing schemas, building and maintaining ETL/ELT pipelines, and shaping the data models that support our products, analytics, and reporting. You will work closely with the Lead Software Engineer to shape technical direction, partnering with teams across the Buyer's Edge Platform product ecosystem on governance, security, and long-term architecture, establishing and holding the team accountable to data standards.

A Minnesota-based company, Real Time Solutions thrives on proactively addressing food service trends, pitfalls, and opportunities, always staying one step ahead. By seamlessly merging data intelligence with marketing finesse, we create campaigns and tactics that are not just reactive but rooted in insightful strategy. As a Buyers Edge Platform brand, our deep food service expertise and data-rich analytics set us apart, allowing us not only to identify growth opportunities for Fortune 500 food manufacturers, but also craft bold strategies and tactics that redefine their success in food service.

This role remotely based .
We are unable to offer work sponsorship for this role.

• Platform Ownership:
  Own the primary relational database platform, including schema design, performance tuning, stored procedures, and lifecycle management for Realtime Solution SQL Server databases and technologies.
• Pipeline Development:
  Architect, build, and maintain ETL/ELT data pipelines that serve as the backbone of the organization's data infrastructure.
• Data Modeling:
  Design data models and schemas that serve multiple application and reporting layers.
• Data Contracts:
  Define and enforce data contracts between source systems and downstream consumers.
• Security & Compliance:
  Implement solutions that follow data governance and security compliance best practices, including PII handling, role-based access controls, audit logging, and encryption at rest/in transit.
• Disaster Recovery:
  Own or contribute to disaster recovery, backup strategy, and restore procedures for the data platform.
• Release Management:
  Manage schema change deployments across environments (dev to staging to prod), including migration scripts and release coordination.
• Documentation:
  Maintain comprehensive documentation, including data dictionaries, pipeline runbooks, architecture diagrams, and data flow maps.
• Continuous Improvement:
  Evaluate and recommend tools, frameworks, and technologies to improve the data platform.
• Technical Mentorship:
  Mentor and guide junior engineers and analysts on data engineering best practices, SQL proficiency, and pipeline design.
• Growth & Development:
  Foster a growth environment by supporting skill development through code reviews, pair programming, and knowledge sharing.
• Engineering Standards:
  Champion engineering standards and help elevate the team's overall technical capability.

• SQL Mastery:
  Expert-level proficiency in relational databases, including complex stored procedures, query optimization, indexing strategies, and execution plan analysis.
• Pipeline Architecture:
  Experience designing end-to-end data flows, orchestration, scheduling, error handling, and recovery patterns.
• Data Modeling:
  Strong experience in data modeling, documenting data lineage, and metadata management.
• Scripting:
  Proficiency in a scripting language (Python, JavaScript, or similar) for pipeline tooling and automation.
• Data Quality:
  Ability to implement validation, reconciliation, and monitoring at pipeline boundaries.
• Communication:
  Strong communication skills with the ability to translate data issues into business impact and partner with analysts and product teams.
• Version Control:
  Git-based workflows, PR-based development, versioned schema migrations.
• Self-Direction:
  Ability to work independently with minimal oversight, driving projects from requirements through delivery.
• Experience:
  
  5 years of data engineering experience, including relational databases, APIs, batch/streaming patterns, and cloud data platforms.
• Data Modeling: 3 years of experience in data modeling, documenting data lineage and metadata.
• Stored Procedures:
  Demonstrated experience building and maintaining complex stored procedures in a production environment.
• Orchestration: 3 years of experience with pipeline orchestration or scheduling tools (SSIS, Airflow, Databricks, or similar).
• Education:
  
  Bachelor's degree in Computer Science, Information Systems, or a related field, or 5 years equivalent software…