Senior Business Intelligence Engineer

Converge Resources, Inc.; Dallas (TX); Hybrid; USD 110,000 - 170,000; Full time

Job summary

Converge Resources, Inc. seeks a hands-on Data Warehouse/BI Engineer to design dimensional models, build T-SQL and ETL pipelines, and own production data reliability. You will collaborate with business partners to translate reporting needs into scalable, secure data solutions across SQL Server, Azure, and Power BI environments.

The role emphasizes migrating legacy systems to modern cloud platforms, maintaining documentation, and contributing to a data-driven culture with strong SCRUM processes.

Qualifications

• 7+ years hands-on data warehouse / BI engineering experience.
• 5+ years designing dimensional models with Kimball.
• 5+ years advanced T-SQL and query tuning on large tables.
• 4+ years building ETL/ELT pipelines with SSIS, ADF, Fabric, or Synapse.
• 3+ years supporting production data environments and root cause analysis.
• 2+ years with semantic/analytical models (SSAS Tabular, Power BI).
• Experience with source control and Scrum release management.
• Strong business-facing communication for requirements gathering.

Responsibilities

• Define, design, and maintain dimensional data models and warehouse architecture.
• Build and optimize ETL/ELT pipelines with incremental loads and restartability.
• Develop semantic/analytical models including measures and row-level security.
• Own production reliability: monitoring, logging, and alerting for pipelines.
• Migrate legacy warehouse logic to modern cloud platforms (Azure).
• Collaborate with SMEs to translate requirements into data solutions.
• Maintain technical docs, code reviews, and release processes in Scrum.

Skills

Data warehouse

BI engineering

Kimball modeling

T-SQL

ETL pipelines

Azure Data Factory

Semantic models

Power BI

SSAS Tabular

Azure DevOps

SQL Server

Education

Bachelor's degree in CS / MIS / Data Eng

Tools

SQL Server

Dataverse

Excel

Azure SQL

SharePoint

Tableau

SSIS

Microsoft Fabric

Power BI

Azure Data Factory

Job description

In this role, you will design and build the dimensional models — the fact and dimension tables, star schemas, and the T‑SQL and ETL behind them — that the business runs on. You will translate business reporting needs into well‑architected, efficient data models, working directly with business partners rather than receiving finished structures from a separate engineering team. You will also build the semantic models and the operational framework that make those models trustworthy in production. This role will drive innovation, enhance user experience, and enable data democratization across the organization.

This is a hands‑on engineering role. You will personally write the T‑SQL, build the pipelines, and own the results.

Location

Hybrid in the Dallas, TX area: onsite Monday, Tuesday, and Thursday, with Wednesday and Friday remote. Team or business needs may occasionally require additional onsite days.

Key Responsibilities

• Define, design, develop, document, and maintain dimensional data models and data warehouse architecture, personally building the fact and dimension tables, star schemas, and source‑to‑target mappings.
• Oversee and perform analysis, design, implementation, and support of the company data warehouse, including developing ETL/ELT routines with appropriate tools — handling incremental loads, historical data, restartability, error handling, and load‑order dependencies.
• Build and maintain semantic and analytical models (SSAS Tabular and Power BI semantic models), including measures, hierarchies, refresh orchestration, and row‑level security.
• Own production reliability for the data warehouse: monitor pipeline and cube processing runs, build audit, logging, and alerting frameworks, investigate failures, document root cause, and implement corrective action.
• Work across data sources such as SQL Server, Dataverse, Excel, Azure SQL, SharePoint, API‑based data, and unstructured data.
• Migrate legacy warehouse logic (SQL Server, SSIS, SSRS, Tableau) onto the modern Azure SQL Managed Instance and Microsoft Fabric platform.
• Maintain data integrity, ongoing solution quality, and adherence to security, architectural, and usability standards; perform data profiling, validation, and reconciliation, and resolve data quality issues with the relevant teams.
• Collaborate with subject‑matter experts, often in ambiguous situations, to determine business information and reporting requirements.
• Maintain technical documentation — source‑to‑target mappings, ETL specifications, job dependencies, and deployment notes — and participate in code review, source control, and release management within a Scrum process.
• Build and maintain relationships with technology teams and business partners to align technology initiatives with business strategy.
• Provide technical and architectural guidance to ensure effective reporting and analysis.
• Stay current on new technologies through continuous learning, industry publications, vendor contacts, and training.
• Other duties as assigned.

Basic Qualifications

• 7+ years of hands‑on data warehouse / BI engineering experience — you have personally built these solutions, not only directed or coordinated others who did.
• 5+ years designing and building dimensional models using Kimball methodology, including fact and dimension tables, star schemas, and source‑to‑target mapping. You can explain grain, surrogate keys, slowly changing dimension types, and conformed dimensions from your own work.
• 5+ years of advanced T‑SQL: complex queries, stored procedures, views, functions, indexes, execution plan analysis, and query tuning against large tables.
• 4+ years building and deploying ETL/ELT pipelines end to end with SSIS, Azure Data Factory, Microsoft Fabric, or Synapse — including incremental loads, historical data handling, restartability, error handling, and load‑order dependencies.
• 3+ years supporting production data environments: monitoring job runs, investigating failures, documenting root cause, and implementing corrective action.
• 2+ years with semantic and analytical models — SSAS Tabular, Power BI semantic models, DAX measures, refresh orchestration, and row‑level security.
• Thorough understanding of data warehouse architecture, data modeling, security, and usability principles.
• Experience with source control and release management (Azure DevOps or Git), code review, and working within Scrum sprints.
• Business‑facing communication — demonstrated ability to gather requirements directly from business SMEs in ambiguous situations and translate them into a modeled, documented reporting solution, communicating clearly with both business and technical partners.
• Comfort with ambiguity and competing objectives in a fast‑paced, collaborative, team‑oriented environment.

Preferred Qualifications

• Bachelor's degree in Computer Science, Management Information Systems, Data Engineering, Information Technology, Engineering, or a related field; equivalent professional experience will be considered in place of a degree.
• Microsoft certification such as Fabric Analytics Engineer Associate, Azure Data Engineer Associate, or Azure Database Administrator Associate.
• Microsoft Fabric, Azure Synapse, Azure Data Factory, Databricks, and/or SSIS. Strength in the modern stack can offset lighter experience in the legacy stack, and vice versa.
• Azure SQL Database, Azure SQL Managed Instance, on‑premises SQL Server, and Azure DevOps.
• Azure services including Azure Data Lake; CI/CD build and release pipelines; implementing API‑based data integrations.
• Experience migrating a legacy warehouse (SQL Server, SSIS, Tableau) to a modern cloud platform.
• Working with varied sources: SQL Server, Dataverse, Excel, Azure SQL, SharePoint Lists/Libraries, API‑based data, and unstructured data.
• Manufacturing data; knowledge of D365 Finance and Operations data structures.