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What is the difference between Talentmovers vs Recruiter?

AspectTalentmoversRecruiter
Primary RoleConnects job seekers with opportunities, often focusing on talent sourcing and placementIdentifies, attracts, and screens candidates for specific job openings
Required CredentialsVaries; often includes HR or recruiting certifications, strong communication skillsHR certifications, recruiting experience, knowledge of hiring practices
Work EnvironmentRecruitment agencies, corporate HR departments, online platformsCorporate HR teams, staffing agencies, recruitment firms

While both Talentmovers and Recruiters focus on connecting candidates with jobs, Talentmovers often emphasize broader talent sourcing and employer branding, whereas Recruiters typically focus on filling specific roles efficiently. Understanding these differences helps job seekers and employers choose the right partner for their hiring needs.

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Infographic showing various Talentmovers job openings in Texas as of August 2026, with employment types broken down into 100% Contract. Highlights an 100% In-person job distribution.

senior Azure Data Engineer::Dallas TX(Onsite)

talentmovers inc

Dallas, TX • On-site

$113K - $136K/yr

Contractor

Re-posted 28 days ago

Job description

Title : Azure Data Engineer 

Location : Dallas, TX(Onsite)

Rate: on C2C/W2/Full time 

Expereince : 12 + Years 

 Mandatory skills:

  • Azure Data Factory
  • Azure Synapse
  • SQL
  • Pyspark
  • Rest API
  • ADLS Gen2/Blob 

Excellent interpersonal and communication skills (written as well as verbal)  

Must have a positive attitude, attention to detail, be a team player, possess good problem solving skills, and have a strong work ethic

Ability and desire to learn and work with new technologies as needed.

 Job Summary:

The Azure Data Engineer (Senior) is a highly experienced role responsible for leading the design, development, and maintenance of large-scale, complex data processing systems on the Azure platform. They work with data architects, data scientists, and other stakeholders to ensure data solutions are scalable, reliable, and secure.

Job Description:

Job Responsibilities

·       Design and implement Data Ingestion from multiple sources to Azure Data Storage services.

·       Implement Azure data services and tools to ingest, egress, and transform data from multiple sources.

·       Responsible for creating an ETL pipeline with Azure Ecosystem like Azure Data Bricks, Azure Data Factory.

·       Build simple to complex pipelines, activities, Datasets & data flows

·       Utilize Azure compute services [Databricks, Data Lake Store, PySpark, Apache Spark, Synapse, Data Factory] to implement transformation logic and stage transformed data.

·       Design data ingestion into data modelling services to create cross domain data models for end user consumption.

·       Implement ETL, related jobs to curate, transform and aggregate data to create source models for end user analytics use cases.

·       Scheduling automation and monitoring instrumentation for data movement jobs.

·       Working experience with Azure monitor and Azure log Analytics.

·       Background work on legacy data warehouses and Big Data will be plus.

·       Should have fair knowledge of the consumption layer (BI) and the business processes.

·       Implement/Support Azure DBaaS infrastructure and services

·       Experience working in Agile/Scrum/Kanban team environments

Candidate Profile / Qualification

·       A Minimum of a Bachelor’s degree in Computer Science or related software engineering discipline, or equivalent

·       7-9 years of experience managing SQL Queries, Data Lake, Data Bricks, PySpark, Synapse, Data factory etc.

·       Strong ETL pipeline development experience with Azure Ecosystem like Azure Data Bricks, Azure Data Factory. Build simple to complex notebooks, pipelines, activities, Datasets & data flows.

·       Experience with message ingestion systems like Kafka / Azure Event Hub.

·       Experience in data modelling and Proficient in SQL developer skills in writing stored procedures, functions, transformations etc.

·       Experience in PySpark and data factory is must

·       Knowledge in Service provisioning, scripted provisioning, blueprint development for data service deployment etc.

·       Excellent oral and written communication skills.

·       Candidate should possess a strong work ethic, good interpersonal and communication skills, and a high energy level