Senior Data Engineer

Foundation Software•Strongsville, OH

About The Position

We are a Microsoft heavy organization looking to build out and modernize our data ecosystem. We are seeking a Senior Data Engineer to help design, build, and establish the engineering standards for our data platform. This role requires a hands-on engineer with strong experience in data architecture, data modeling, ETL/ELT, cloud data platforms, and modern data engineering practices. The Senior Data Engineer will design and implement scalable data pipelines, data models, and data platform solutions that support analytics, business intelligence, AI, and enterprise reporting. The role will also help establish best practices for data engineering, reliability, performance, governance, and deployment while partnering closely with business stakeholders, analysts, and technology teams. This is a hands-on role for an experienced engineer who can move effectively from architecture and design through implementation and production support. We need someone who has done this before, understands what good looks like, and can help shape how we build, operate, and evolve our data environment.

Requirements

Bachelor's degree in Computer Science, Data Engineering, Mathematics, or related field.
7+ years of hands-on experience in data engineering or a closely related discipline.
Expert-level SQL skills in database design, dimensional modeling, query optimization, indexing, and performance tuning.
Experience with modern cloud data warehouses (Fabric Warehouse, BigQuery, Databricks, etc.), including Lakehouse architectures and large-scale data processing platforms.
Strong experience designing logical and physical data models including star and snowflake schemas.
Background implementing CI/CD pipelines and automated deployment practices ( g. DevOps, GitHub Actions).
Experience with programming skills in languages commonly used in data engineering (e.g. Python, Java, or Scala).
Excellent experience with modern ETL/ELT orchestration tools (e.g. Fivetran, Azure/Fabric Data Factory, and dbt or similar tools).
Strong experience and knowledge with cloud platforms and data services (e.g. AWS, Azure, Fabric).
Proficient with version control systems (e.g. GitHub or Azure DevOps).
Experience with BI tools (e.g. Microsoft Power BI or Tableau).
Comfortable working independently in a dynamic environment, managing multiple priorities even in the face of ambiguity or evolving requirements.

Responsibilities

Architect, build, and manage data repositories, data integration solutions, and scalable pipelines.
Implement CI/CD practices for data pipelines and transformations.
Design and implement monitoring, alerting, observability, and operational support processes for data pipelines and platforms.
Troubleshoot and resolve data pipeline failures, performance bottlenecks, and production incidents.
Assist in the evaluation, selection, deployment, and maintenance of data infrastructure components, including databases, data platforms, and pipeline tools.
Create, maintain, and evolve logical and physical dimensional data models and schema designs in support of storage, retrieval, and analytics.
Optimize data storage, processing, and query performance while managing cloud infrastructure costs.
Execute strategies for workload tuning, partitioning, indexing, and resource utilization.
Implement robust data validation, quality checks, and metadata management to monitor data accuracy, consistency, and reliability across pipelines aiding analytics, BI, and AI requirements.
Ensure data governance policies, compliance requirements, and security requirements are met by design as code.
Maintain proficiency with technology trends in data engineering, evaluating potential impacts.
Document data architectures, infrastructure designs, pipelines, workflows, transformations, and data models for both technical and non-technical audiences.
Collaborate with business and technical stakeholders to define requirements, prioritize initiatives, and deliver trusted, scalable data products and services.
Mentor and coach team members while promoting engineering best practices, technical standards, and continuous improvement.