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We are partnered with an innovative HealthTech company in Dallas that is transforming healthcare through advanced data-driven solutions. They are now seeking a talented Data Scientist to join their growing team and help tackle some of the most impactful challenges in healthcare today.

Role Overview:

As a Data Scientist, you will work closely with product, engineering, and clinical teams to develop models and insights that drive better patient outcomes, optimize operations, and enable new product offerings. This is a hands-on role where you will have the opportunity to work with diverse healthcare data sets and apply the latest machine learning and statistical techniques.

Key Responsibilities:



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Design, build, and deploy predictive models to improve patient care and operational efficiency
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Analyze large-scale healthcare data sets (EMR, claims, device data, etc.)
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Collaborate with cross-functional teams to turn insights into actionable product features
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Communicate findings to both technical and non-technical stakeholders
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Stay current with new developments in machine learning, AI, and healthcare analytics



Ideal Candidate:



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5+ years experience in data science or machine learning, preferably in healthcare or life sciences
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Strong programming skills in Python (Pandas, Scikit-learn, etc.)
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Solid understanding of statistical methods, machine learning techniques, and data wrangling
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Experience working with healthcare data sets (FHIR, HL7, claims, EMR) is a plus
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Strong communication skills and ability to thrive in a collaborative environment



Why Join?



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Make an impact on real-world healthcare outcomes
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Work with a collaborative, mission-driven team
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Hybrid work flexibility (Dallas HQ)
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Competitive salary and benefits

This role focuses on building scalable data pipelines, integrating diverse data sources, and enabling predictive analytics across cloud environments.



Key Technical Requirements:

* Strong hands-on experience developing data pipelines using Python
* Strong SQL skills, including performance tuning, stored procedures, and data modeling (Star/Snowflake schemas)
* Proven experience with Azure Data Factory (ADF) and Azure Synapse
* Experience with ETL orchestration tools such as Apache Airflow
* Skilled in working with structured and unstructured data, including ingestion from APIs (REST/JSON/XML)
* Familiarity with cloud-based warehousing tools such as Snowflake, Redshift, or BigQuery
* Comfortable working in Azure and/or hybrid cloud environments (Azure/AWS)
* Experience supporting machine learning or predictive modeling pipelines
* Familiar with containerization and version control: Docker, Git, and Azure DevOps
* Understanding of data serialization formats (Parquet, Avro, JSON)
* Knowledge of data validation, quality checks, and observability tools (Azure Monitor, logging frameworks, etc.)



Candidates will be expected, during the interview process, to demonstrate deep hands-on technical experience in data pipeline development, cloud orchestration, and ML-ready data infrastructure.



This position will require the successful applicant to work 5 days per week on site.

Position Title: Data Engineer

About the Role:

We're seeking a dynamic and resourceful Data Engineer to become part of our expanding team. In this role, you'll be responsible for building and maintaining robust, scalable data pipelines and infrastructure that support analytics and reporting across the organization. You'll partner with both technical and business teams to ensure data flows efficiently, systems are dependable, and our data strategy is future-ready. The right candidate thrives in a fast-paced environment, is a collaborative problem-solver, and brings a sharp, adaptable mindset to technical challenges.

What You'll Do:

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Pipeline Engineering: Develop and maintain scalable ETL/ELT workflows to support data needs across analytics, operations, and business functions.
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Infrastructure Design: Architect and fine-tune data platforms across cloud and hybrid environments for optimized access and performance.
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Cross-Functional Collaboration: Partner with data scientists, analysts, engineers, and product teams to deliver reliable, actionable data solutions.
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System Performance: Ensure systems are built with scale in mind, proactively managing performance and growth.
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End-to-End Ownership: Manage the full data lifecycle-from ingestion through transformation and delivery-without handoffs or silos.
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Data Quality & Compliance: Uphold data integrity, security, and traceability in line with internal and regulatory standards.
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Innovative Problem Solving: Navigate evolving challenges with a solution-oriented mindset and flexible approach to tools and technologies.
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Team Engagement: Contribute to a small, high-impact team where every voice counts and initiative drives progress.

What We're Looking For:

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Education: A bachelor's degree in Computer Science, Engineering, or a related discipline (advanced degrees welcomed).
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Professional Experience: Solid background in data engineering across data ingestion, transformation, and storage layers.
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Technical Proficiency: Strong command of SQL and experience with at least one core technology (e.g., Python, Scala, Spark, Snowflake, AWS, etc.).
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Adaptability: Comfortable working in changing technical landscapes and open to evolving tools and priorities.
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Data Architecture Knowledge: Deep understanding of database systems, data modeling practices, and cloud-based infrastructure.
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Workflow Tools: Experience with orchestration tools like Airflow, dbt, or comparable systems.
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Nice to Have: Familiarity with business intelligence platforms such as Power BI, Tableau, or MicroStrategy.

Key Attributes:

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Proactive and solution-focused, not afraid to take ownership.
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Strong analytical and systems thinking skills with a practical mindset.
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Clear communicator who can articulate technical ideas to various audiences.
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Team player who can also thrive in independent settings.
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Detail-oriented, reliable, and invested in the team's and company's success.
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Agile and professional under pressure, with a flexible approach to shifting priorities.

A leading US technology company is building a new event-driven platform powered by serverless AWS services and applied AI. The team operates in a fast-paced, start-up style environment and is expanding its engineering group to accelerate green-field product development.

As a Senior Back-End Engineer you will design, implement and operate Node.js workloads running in AWS Lambda behind API Gateway. You will modernize legacy endpoints, create new APIs, and embed AI capabilities such as LLM-driven features into production systems. Daily work includes writing infrastructure as code, optimizing cold-start performance, managing data in DynamoDB and PostgreSQL, and owning the full service lifecycle from code to monitoring. You will collaborate with a hands-on technical leadership team and influence architecture choices across multiple agile pods.

Technical requirements

* Deep competence with Node.js for back-end development.
* Production experience deploying and operating AWS Lambda functions and Amazon API Gateway integrations.
* Proficiency with serverless design patterns, event buses, and infrastructure-as-code tools such as AWS SAM, CDK, or Terraform.
* Knowledge of data stores suitable for serverless workloads, especially DynamoDB and PostgreSQL.
* Hands-on work integrating AI or machine-learning services into live applications and a strong interest in advancing those capabilities.
* Ability to optimize performance, security, observability, and cost in a serverless environment.

This role focuses on building scalable data pipelines, integrating diverse data sources, and enabling predictive analytics across cloud environments.



Key Technical Requirements:

* Strong hands-on experience developing data pipelines using Python
* Strong SQL skills, including performance tuning, stored procedures, and data modeling (Star/Snowflake schemas)
* Proven experience with Azure Data Factory (ADF) and Azure Synapse
* Experience with ETL orchestration tools such as Apache Airflow
* Skilled in working with structured and unstructured data, including ingestion from APIs (REST/JSON/XML)
* Familiarity with cloud-based warehousing tools such as Snowflake, Redshift, or BigQuery
* Comfortable working in Azure and/or hybrid cloud environments (Azure/AWS)
* Experience supporting machine learning or predictive modeling pipelines
* Familiar with containerization and version control: Docker, Git, and Azure DevOps
* Understanding of data serialization formats (Parquet, Avro, JSON)
* Knowledge of data validation, quality checks, and observability tools (Azure Monitor, logging frameworks, etc.)



Candidates will be expected, during the interview process, to demonstrate deep hands-on technical experience in data pipeline development, cloud orchestration, and ML-ready data infrastructure.



This position will require the successful applicant to work 5 days per week on site.

This is an opportunity to join a growing business in the Engineering and Manufacturing space and take ownership of the full Power BI lifecycle. In this role you will connect to sources, shape data with Power Query/M, build star-schema models, write advanced DAX, design visuals, and publish to the Service.



Candidates must be able to demonstrate strong experience in such roles prior to this one. Candidates will also be expected to demonstrate experience with:

* Building and maintaining enterprise-grade ETL pipelines with SSIS, Azure Data Factory, or similar to feed a data warehouse / data lake.
* Designing scalable tabular / SSAS models and implementing row-level security on large datasets.
* Optimizing report and query performance on high-volume platforms such as Snowflake or SQL Server.
* Administering workspaces, gateways, scheduled refresh, and usage monitoring in Power BI Service.
* Extending solutions with the wider Microsoft stack (Power Apps, Power Automate, Azure Data Lake) for end-to-end analytics workflows.



Must-have technical skills

* Prior experience developing enterprise Power BI solutions.
* Expert DAX and M query; creating complex KPIs and time-intelligence measures.
* Strong SQL (T-SQL, Snowflake SQL) and performance tuning.
* Hands-on experience with SSIS or Azure Data Factory ETL workflows.
* Proven ability to model data in star / snowflake schemas and secure it with RLS.
* Experience managing Power BI gateways, incremental refresh, and CI/CD of BI assets (DevOps or Git).

Technical Responsibilities

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Own the end-to-end design and rollout of AI solutions that accelerate sales forecasting, quote generation, and marketing content creation.
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Map current processes in Microsoft Dynamics 365 Business Central (BC); identify data sources, gaps, and integration points for AI.
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Architect and implement Azure-based services (Azure OpenAI Service, Cognitive Services, Azure Machine Learning, Data Factory, Synapse, Functions, Logic Apps) to ingest data, train models, and deploy scalable, secure APIs.
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Build and maintain reusable forecasting and CPQ models, prompt libraries, and generative-content templates; establish CI/CD and MLOps pipelines.
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Define and enforce AI governance: data quality standards, versioning, telemetry, bias mitigation, security, and Responsible AI compliance.
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Lead backlog grooming, sprint planning, and cross-functional collaboration with product, marketing, and IT; serve as the technical lead for adoption of AI across the organization
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Track and report performance metrics (latency, accuracy, ROI) and continuously optimize models and workflows.

Required Skills & Experience

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Successful track record of delivering data analytics / software solutions, with recent lead role(s) in production AI/ML and/or generative-AI deployments.
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Deep expertise in Azure AI stack (Azure OpenAI, Cognitive Services, Azure Machine Learning, Data Lake, Synapse, Data Factory) and in designing secure, high-availability cloud architectures.
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Hands-on knowledge of Microsoft Dynamics 365 Business Central APIs, AL extensions, and Power Platform (Power Automate, Power Apps, Copilot Studio, Dataverse).
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Strong programming background (Python, SQL) and proficiency with Git-based CI/CD, RESTful API design, and serverless/event-driven patterns.
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Proven delivery of forecasting, CPQ, or marketing-content AI solutions at enterprise scale; fluency in prompt engineering, retrieval-augmented generation, and vector databases (e.g., Azure Cosmos DB, Elastic).
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Experience standing up MLOps frameworks (MLflow, Azure ML pipelines) and monitoring for model drift, data shifts, and cost efficiency.
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Solid grasp of data governance, privacy (GDPR/CCPA), security best practices, and Responsible AI principles.
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Exceptional stakeholder-management and leadership skills; adept at evangelizing new technology and mentoring engineers in an agile environment.



This position is on-site in Dallas, specifically in the vicinity of Grapevine so candidates must be local, and willing to work onsite 5 days per week.

Position Title: Data Analyst

Job Overview:

The Data Analyst will support data analysis and reporting efforts, handling everything from data acquisition to generating insights. This role involves working with technical teams to extract and analyse data from the company's central repository using advanced reporting tools. The Analyst will provide actionable insights and recommendations that help inform decision-making processes across the organization.

Key Responsibilities:

* Data Analysis & Reporting: Analyse organizational performance and trends, identifying significant patterns, outliers, and factors that impact outcomes.

* Insight Generation: Investigate data to reveal patterns and behaviours that can inform business decisions and improve overall performance.

* Strategic Recommendations: Provide recommendations based on analysis to assist leadership with both strategic and operational decisions via white papers.

* Reporting & Presentations: Prepare and present reports to key internal and external teams via power point, helping guide data-driven decision-making.

* Validation Studies: Conduct studies using external data sources to support the company's overall value proposition.

* Data Strategy Development: Propose and implement strategies to enhance data management, accessibility, and reporting processes.

* Technical Tools Usage: Leverage reporting tools such as MicroStrategy to generate in-depth reports and analyses from the data warehouse.

* Flexible Role: This job description outlines the general responsibilities, but additional tasks may arise as needed.

Qualifications:

* Education: Bachelor's degree in Computer Science, Information Technology, or a related field (graduate degree preferred).

* Experience: Experience in data analysis, with a strong background in handling large data sets and proficiency with tools such as SPSS, MS-SQL, PL/SQL, SQL, Access, or Python.

* Experience with data visualisation and reporting tools like Power BI, MicroStrategy, or Tableau is essential.

* Ability to independently manage tasks and offer support to junior team members when needed.

* Strong project management and presentation skills are crucial.

Skills & Competencies:

* Demonstrates core values such as attention to detail, initiative, and adaptability.

* Strong problem-solving abilities, with a logical approach to analysing data and providing solutions.

* Excellent communication and interpersonal skills, able to present data clearly and professionally.

* Capacity to handle confidential information, ensuring compliance with policies and regulations.

* Advanced proficiency in Microsoft Office and other related software.

* In-depth experience working with database tools and providing technical recommendations to streamline processes.

* Flexible and adaptable to changing priorities, with the ability to meet deadlines in a fast-paced environment.

Power BI Developer

Build, Govern, and Ship with Git-Driven Pipelines

An award winning, Dallas based, organization has the opportunity for an experienced, and passionate, Power BI Developer to join the team on a permanent basis. With the analytics run on carefully crafted semantic models they are looking for someone who can bring a passion for Power BI and utilize that to keep those models fast, accurate, and fully traceable.

This role is based out of the organizations offices in the North Dallas / Galleria area - and requires 4 days per week on site, with Friday being the remote work day.



What you'll do

* Shape raw warehouse data into clean tabular models, write reusable DAX, and publish pixel-perfect reports.
* Commit every change to Git, pass automated Tabular Editor checks, and promote through gated Dev, Test, Prod pipelines
* Enforce a "work-item + approval" rule; nothing reaches production without a green build and your pull-request notes
* Stay plugged into monthly Power BI updates, prototype new features, and brief the team on what's worth adopting
* Partner with the hiring manager and the wider data team during roll-outs - answer questions, tweak visuals, and keep dataflows flowing



Tech stack you'll touch

Power BI Desktop & Service, PBIP/TMDL, Tabular Editor, Azure DevOps or GitHub Actions, REST APIs, SQL/Lakehouse sources, incremental refresh, dynamic RLS, partitioning.

A leading entertainment company based in Dallas is seeking a Senior Data Engineer / Architect to help shape and optimize the future of their data architecture. This is a key role in modernizing their analytics platform, with a particular focus on Google BigQuery and cloud-native design.

What You'll Do:

* Design and implement scalable data solutions using BigQuery, optimizing for performance, cost, and maintainability
* Lead the architectural strategy for the company's data platform, ensuring alignment with business needs and best practices
* Migrate legacy systems to a modern BigQuery-based stack
* Collaborate with BI teams, analysts, and stakeholders to ensure data is modeled for reporting and decision-making
* Implement robust data pipelines (ETL/ELT) using tools like Cloud Dataflow, DBT, Apache Beam, or similar
* Establish and enforce data governance, quality, and documentation standards

What We're Looking For:

* Strong experience designing and architecting cloud-based data warehouses, especially with BigQuery
* Expertise in SQL performance tuning and large-scale data modeling
* Proficiency with ETL tools and orchestration frameworks (e.g., Airflow, DBT, Dataflow)
* Familiarity with GCP services and data infrastructure best practices
* Experience working with semi-structured data (e.g., JSON, Parquet)
* Ability to lead and mentor data engineering teams and influence architectural direction