Senior Business Intelligence & Data Engineer

Smith & Wesson; Maryville (TN); On-site; USD 90,000 - 130,000; Full time

Job summary

Smith & Wesson seeks a Modern BI / Data Warehouse Developer to bridge traditional BI engineering with cloud analytics. The role emphasizes data ingestion, modeling and semantic layer readiness for analytics, while not directly building production reports.

You will design scalable data pipelines into Microsoft Fabric, create transformations using notebooks (Python/Pandas) and Spark, and collaborate with analysts to ensure data readiness for self-service BI in a manufacturing environment.

Qualifications

• 3+ years of professional experience in BI, data engineering, or data warehouse development in an enterprise environment.
• 2+ years of hands-on experience with T-SQL, including: complex joins, window functions, CTEs.
• 2+ years of experience designing and implementing ETL/ELT pipelines.
• 1+ years of experience building data pipelines using Azure Data Factory (ADF) or a comparable orchestration tool.
• 3+ years of experience with modern data warehousing principles, including layered architectures (raw, curated, consumption).
• 3+ years of hands-on dimensional data modeling experience, including star and snowflake schemas, and surrogate keys (SCD Type 1/2).
• 1+ years of experience developing data transformations using notebooks.
• Working knowledge of reporting and analytics tools concepts.

Responsibilities

• Design and implement data ingestion pipelines to move data from source systems into Microsoft Fabric (Lakehouse/Warehouse).
• Create and maintain pipelines using Azure Data Factory and Fabric-native orchestration patterns.
• Build transformation logic using notebooks (Python, Pandas, Spark).
• Apply best practices for reproducibility, parameterization, modular notebooks, and version control.
• Optimize performance through partitioning, pushdown, and caching where relevant.
• Design and maintain enterprise data warehouse models for analytics consumption.
• Ensure data models align with BI usage patterns and collaborate with report developers.
• Translate stakeholder requirements into scalable pipelines and data models; participate in code reviews and documentation.

Skills

T-SQL

Relational data modeling

ETL/ELT pipelines

Python/Pandas

Spark

Fabric data patterns

Data warehousing concepts

Query performance tuning

Reporting concepts

CI/CD for data assets

Education

Bachelor's degree in Computer Science, Engineering, or related field

Tools

Azure Data Factory

Microsoft Fabric

Notebook development

Job description

We are looking for a Modern BI / Data Warehouse Developer who can bridge traditional BI engineering (T‑SQL, ETL, SSIS—nice to have) with modern cloud analytics patterns, including building scalable data pipelines into Microsoft Fabric and creating transformations using notebooks (Python/Pandas) and related tooling.

This role focuses on data ingestion, modeling, transformations, and semantic layer readiness. While the role will not be responsible for building production reports, the ideal candidate understands reporting needs well enough to design data models and semantic models that support analytics and self‑service BI.

COMPETENCIES AND SKILLS:

Strong hands‑on experience with T‑SQL and relational data modeling.

Proven experience building ETL/ELT pipelines and supporting production data workflows.

Experience with Azure Data Factory (ADF) or comparable orchestration tools.

Experience building transformations using notebooks, including Python and Pandas (and/or Spark‑based transformations as needed).

Strong understanding of:

modern data warehousing

performance fundamentals (indexes, partitioning concepts, query tuning as applicable)

Working knowledge of reporting concepts (requirements, visual performance considerations, data shaping), even if not building reports.

Nice to have skills:

SSIS experience (nice‑to‑have, not required).

Experience with Microsoft Fabric components (Lakehouse, Warehouse, pipelines, notebooks, shortcuts, etc.).

Familiarity with semantic modeling platforms and patterns (e.g., Power BI semantic models/tabular concepts).

Exposure to data governance, cataloging, and lineage practices.

Experience with CI/CD for data assets (Git integration, environment promotion).

ESSENTIAL DUTIES AND RESPONSIBILITIES:

Design and implement data ingestion pipelines to move data from source systems (SQL, files, APIs, SaaS apps) into Microsoft Fabric (e.g., Lakehouse/Warehouse).

Create and maintain pipelines using Azure Data Factory (ADF) and/or Fabric‑native orchestration patterns as appropriate.

Build transformation logic using notebooks and modern approaches (Python, Pandas, Spark where applicable).

Apply best practices for:

reproducibility (parameterization, modular notebooks, version control)

performance optimization (partitioning, pushdown, caching strategies where relevant)

Design and maintain enterprise data warehouse models

Understand how to prepare data for semantic models and analytics consumption:

Collaborate with report developers/analysts by ensuring data models align with real BI usage patterns.

Work closely with stakeholders (analysts, app teams, data owners) to translate requirements into scalable pipelines and models.

Participate in code reviews, documentation, and operational handoffs.

Help establish standards for naming, versioning, environments, and deployment patterns.

QUALIFICATIONS:

3+ years of professional experience in BI, data engineering, or data warehouse development in an enterprise environment.

2+ years of hands‑on experience with T‑SQL, including:

complex joins, window functions, CTEs

query optimization and performance tuning

building and maintaining transformation logic in SQL

2+ years of experience designing and implementing ETL/ELT pipelines.

1+ years of experience building data pipelines using Azure Data Factory (ADF) or a comparable orchestration tool.

3+ years of experience with modern data warehousing principles, including:

layered architectures (raw, curated, consumption)

ELT patterns batch and incremental loading strategies

3+ years of hands‑on dimensional data modeling experience, including:

star and snowflake schemas

fact and dimension table design

surrogate keys and SCD (Type 1/2) patterns

1+ years of experience developing data transformations using notebooks.

Working knowledge of reporting and analytics tools concepts (e.g., how analysts and business users consume data), even if not responsible for building reports directly.

Professional communications skills, both verbal and written. Good team player.

Manage personal workload and work under tight timeframes.

Must be able to work independently with minimal supervision.

Bachelor’s degree in Computer Science, Engineering, or a related field preferred.

PHYSICAL DEMANDS:

Occasional: bending, kneeling, squatting, standing, walking, reaching, overhead reaching, and fine motor skills

WORK ENVIRONMENT:

Normal office environment and office lighting

Within the Smith & Wesson manufacturing facility employees may be exposed to manufacturing noise, airborne liquid chemicals, fine particulate dust, ambient temperatures, and industrial lighting

All employees are required to apply ergonomic correctness to all job tasks