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Managed Print Services, Office Technology, IT Services

Data Engineer

United StatesOnsiteFull Time$100,000–$160,000 /yrPosted 2 months agoVisa sponsorship available

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Role summary

FlexTG is seeking a Data Engineer to design, build, and maintain data pipelines and platform components within Microsoft Fabric. This role ensures reliable, governed, and performant data for analytics and machine learning, collaborating with IT and business stakeholders. Responsibilities include developing Lakehouse architectures, orchestrating ETL/ELT pipelines, administering Fabric workloads, enabling AI/ML through ML-ready datasets and operationalizing models, managing data governance and quality, and optimizing performance. The position requires 3-5 years of experience, proficiency in Python and SQL, and experience with Microsoft Fabric, data formats like Delta Lake/Parquet, governance tools like Purview, and CI/CD practices.

FlexTG is the largest Brand-Neutral Managed Print Services provider with an industry-leading Nationwide footprint. We are service and solutions professionals, providing support to clients of all sizes and industries from coast to coast. Our vast support network and unique proprietary technology make us more than Best-in-Class - we're in a class of our own.

Position Summary

The Data Engineer is responsible for designing, building, and maintaining data pipelines and platform components within Microsoft Fabric. The role ensures that data used for analytics and machine learning is reliable, governed, and performant. This position works closely with IT teams and business stakeholders to support model development, deployment, and ongoing operations.

The salary range for this role is $100,000- $160,000 dollars

Essential Functions and Responsibilities

Data Platform Development

  • Build and manage Lakehouse architectures in Microsoft Fabric (OneLake, medallion/layered patterns).
  • Develop and orchestrate ETL/ELT pipelines using Data Factory, Spark notebooks, and SQL.
  • Administer and optimize Fabric workloads (capacity, workspaces, items).

AI & ML Enablement

  • Collaborate with database administrators and data analysts to deliver ML-ready datasets, feature stores, and inference pipelines.
  • Operationalize ML models for batch and streaming processing; design CI/CD workflows for deployment.
  • Implement data quality checks, drift monitoring, lineage, and reproducibility for ML pipelines.

Governance & Quality

  • Manage metadata, lineage, and access controls using Microsoft Purview and Fabric governance tools.
  • Define and enforce data quality SLAs, validation rules, and observability (profiling, anomaly detection).

Performance & Optimization

  • Optimize Spark and SQL jobs for scalability and cost efficiency (partitioning, caching, file formats).
  • Monitor pipeline reliability, throughput, and cost; establish alerting, logging, and recovery strategies.

Collaboration & Standards

  • Document engineering standards and create reusable components (templates, notebooks, scripts).
  • Work cross-functionally to align data initiatives with business priorities.
  • Mentor peers on Fabric best practices, data engineering patterns, and ML operations.

Qualifications and Experience

Minimum Qualifications:

  • Bachelor’s degree in Computer Science, Information Systems, or related field.
  • 3–5 years of professional experience as a Data Engineer.
  • Proficiency in Python and SQL for data engineering workflows.
  • Experience with Microsoft Fabric (OneLake, Lakehouse, Data Factory, Spark notebooks) and Power BI integration.
  • Strong understanding of data formats and engines (Delta Lake, Parquet, Spark).
  • Familiarity with governance and security frameworks (Microsoft Purview, RBAC).
  • Experience implementing CI/CD pipelines, Git integration, and automated testing for data solutions.

Preferred Qualifications:

  • Integration of Fabric with Azure services (ADLS, Azure SQL/MI, Event Hubs, Synapse migration).
  • Exposure to feature stores, MLFlow-style tracking, and MLOps concepts (model registry, monitoring).
  • Knowledge of Power BI semantic models, dataset refresh optimization, and Direct Lake/Direct Query patterns.
  • Experience with streaming data architectures (event ingestion, near-real-time scoring) and micro-batch processing.

Supervisory Responsibilities

This position has no supervisory responsibilities.

Physical Requirements

The physical demands described here are representative of those that must be met by an employee to successfully perform the essential functions of this job. The physical requirements for performing the essential functions of this position require the employee to be able to:

  • Sit, stand, kneel, walk, and reach.
  • Be able to lift, push, pull and/or move up to 20 pounds.
  • Read a computer screen and written material.
  • Write, type, and use phone system.

*Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions**.*

Work Environment

Good working environment with the absence of disagreeable conditions. The noise level in the work environment is usually moderate.

Disclaimer

This job description is not designed to cover or contain a comprehensive list of activities, duties or responsibilities that are required of the employee. Duties, responsibilities, and activities may change, or new ones may be assigned at any time with or without notice. The job description does not constitute an employment contract or guarantee of employment. The organization reserves the right to hire, fire, or discipline the employees at its discretion.

EEO Statement

FlexTG provides equal employment opportunities to all employees and applicants for employment. The Company prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, sexual orientation, gender identity or expression, national origin or ancestry, citizenship or immigration status, physical or mental disability, genetic information (including testing and characteristics), pregnancy (including childbirth, lactation and related medical conditions), protected veteran status, uniformed servicemember status, or any other characteristic protected by federal, state or local laws. This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, benefits, leaves of absence, compensation and training.

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