Data Analytics Engineer

DEXTER TECHNOLOGIES INC; Houston (TX); Hybrid; USD 95,000 - 130,000; Full time

Benefits offered by this job

Dental insurance

Health insurance

Vision insurance

Job summary

DEXTER TECHNOLOGIES INC in Houston is seeking a Data Analytics Engineer to bridge data engineering and business intelligence. You'll write and optimize SQL, build staging tables, views, and fact/dimension models in an Azure SQL data warehouse, and develop semantic models and reports in Power BI.

You will monitor Azure Data Factory pipelines, troubleshoot failures, and collaborate with stakeholders across Finance and Operations to deliver accurate, well-modeled data.

Qualifications

• 3+ years in a data-focused role with hands-on SQL work.
• Experience building semantic models in Power BI.
• Knowledge of dimensional modeling and data warehousing concepts.
• Ability to translate requirements into working data models with stakeholders.
• Strong attention to data integrity and join logic.

Responsibilities

• Data modeling & SQL: design and maintain SQL views, staging tables, and fact/dimension models in Azure SQL.
• Semantic models & reporting: build Power BI semantic models and reports for stakeholders.
• Pipeline support: monitor Azure Data Factory pipelines and Power BI refreshes; troubleshoot failures.
• Pipeline modifications: make minor changes to existing pipelines for evolving needs.
• Business partnership: translate reporting requests into accurate data models with SMEs.
• Documentation: document data models, metrics, and report logic for traceability.
• Standards & quality: contribute to naming conventions and semantic model design.

Skills

SQL

Power BI

Dimensional modeling

Stakeholder engagement

Data quality

Education

Bachelor’s degree in Computer Science or related

Master’s degree a plus

Tools

Azure Data Factory

Git

Python

Job description

Benefits:

• Dental insurance


• Health insurance


• Vision insurance

Hi,

We are actively seeking qualified candidates for the following position for our client, who is an industry leader:

Data Analytics Engineer

Location: Houston TX (4 days in office)

Type: Full Time

This role is a hybrid, bridging the gap between data engineering and business intelligence. You'll spend part of your time writing and optimizing SQL — building staging tables, views, and fact/dimension models — and part of your time building semantic models and reports in Power BI. Keeping an eye on our scheduled data pipelines, you’ll handle first-line troubleshooting when something fails. You'll work closely with the Sr. Manager, Data & Analytics, and with business stakeholders across Finance, Operations, and other functions who depend on accurate, well-modeled data.

This is a great fit for someone who wants breadth — real ownership across the data stack — on a team small enough that your work visibly matters.

Key Responsibilities

• Data modeling & SQL: Design, build, and maintain SQL views, staging tables, and fact/dimension models in our Azure SQL data warehouse, including deduplication and business-rule logic (e.g., status-based routing, multi-source reconciliation).


• Semantic models & reporting: Build and maintain Power BI semantic models — relationships, DAX measures, security roles — and the reports and dashboards built on top of them for business stakeholders and company-wide reporting.


• Pipeline support: Share responsibility with the Sr. Manager, Data & Analytics for monitoring scheduled Azure Data Factory pipelines and Power BI dataset refreshes. Respond to failures and perform basic troubleshooting.


• Pipeline modifications: Make minor modifications to existing pipelines to support new or changing business requirements, as your familiarity with the tooling grows.


• Business partnership: Partner with business SMEs to translate reporting requests and business logic (commission structures, revenue recognition, inventory rules, etc.) into accurate, well-documented data models.


• Documentation: Write and maintain documentation for data models, metric definitions, and report logic so that data lineage and ownership are clear beyond any one person.


• Standards & quality: Follow and help evolve team standards for naming conventions, DAX style, and semantic model design as the team's practices mature.

• Continuous Improvement: Proactively identify opportunities for process improvements, optimize current data workflows, and incorporate new technologies or tools to enhance data analytics capabilities.

Knowledge and Skills

Required

• 3+ years in a data-focused role (analytics engineer, BI developer, data analyst, or similar) with hands-on SQL work — comfortable with CTEs, window functions, and reading/writing complex, multi-source views.


• Solid Power BI experience beyond report formatting — you've built semantic models from scratch and written DAX involving CALCULATE, filter context, and context transition, not just basic aggregations.


• Dimensional modeling fundamentals (star schemas, slowly changing dimensions).


• A track record of working directly with business stakeholders to translate ambiguous requirements or business rules into a working data model.


• Strong attention to detail with data integrity — you double-check your joins and know how a bad join or an inclusive date boundary can quietly break a report.

Preferred

• Exposure to an ERP or other core business system as a data source (order, invoicing, or GL data) - you understand that business rules, not just dates, often drive how records should be deduplicated or classified.


• Understanding of ETL/ELT concepts and working knowledge of orchestration tools like Azure Data Factory or similar tools for automating data pipelines.


• Familiarity with Microsoft Fabric Administration and Environment (Lakehouses, Dataflows Gen2) — not required, but a plus given our platform direction.


• Basic Git / source control experience.


• Python for data tasks.

• Knowledge of data quality frameworks and data governance practices.

Qualifications

• Bachelor’s degree in Computer Science, Data Science, Information Systems, or a related field. Master’s degree is a plus.


• 3+ years in a data-focused role (analytics engineer, BI developer, data analyst, or similar) with hands-on SQL work — comfortable with CTEs, window functions, and reading/writing complex, multi-source views.

Flexible work from home options available.