We are seeking a highly skilled Senior Data Engineer & Analyst with deep, hands-on expertise in Microsoft SQL Server. This role is ideal for someone who can own data pipelines end-to-end—designing, optimizing, and maintaining complex SQL systems—while also delivering high-quality analytics, dashboards, and business insights.
You will work closely with operations, engineering, and business stakeholders to ensure the data ecosystem is efficient, reliable, and ready to support decision-making at scale.
Design, build, and optimize ETL/ELT pipelines using SQL Server, SSIS, or similar tooling.
Develop highly efficient stored procedures, functions, triggers, and views for transactional and analytical workloads.
Architect and maintain data models, schemas, and data warehouses following best practices.
Perform data quality checks, validation routines, and troubleshoot data inconsistencies.
Create dashboards, reports, and KPIs using SQL Server Reporting Services (SSRS) or BI tools (Power BI preferred).
Optimize database performance: indexing, partitioning, query tuning, and monitoring.
Collaborate with cross-functional teams to understand data needs and translate them into scalable solutions.
Ensure security, compliance, and governance of data assets.
Lead and mentor junior engineers or analysts when needed.
Implement automation for repetitive tasks to improve efficiency and accuracy.
7+ years working with SQL Server in data engineering or data analytics roles.
Mastery of T-SQL, complex queries, and performance optimization.
Strong experience building ETL processes (SSIS, Azure Data Factory, or similar tools).
Solid knowledge of data warehousing concepts (star schema, dimensional modeling).
Experience with Power BI or similar BI tools for dashboards and visualizations.
Familiarity with Azure SQL, cloud migrations, or hybrid data environments.
Strong analytical mindset and ability to translate technical insights into business impact.
Excellent communication skills and ability to collaborate with non-technical stakeholders.
Experience in Azure Synapse, Databricks, or Python for data workflows.
Knowledge of APIs, data ingestion, and real-time streaming.
Background in building internal data platforms or self-service analytics.
Experience supporting operational teams (sales, staffing, finance, etc.).