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Data Engineer

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Data Engineer designing Azure, Fabric, Power BI, and Databricks platforms for Reply’s digital transformation clients. Building scalable pipelines, lakehouse architectures, and analytics solutions.

Posted 8/21/2026full-timeAtlanta • Montana, Pennsylvania • 🇺🇸 United StatesMid-LevelSeniorWebsite

Core Competencies

Role fit
Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in designing and optimizing data platforms using Microsoft Azure, Databricks, and Power BI, with a strong focus on data ingestion, transformation, and governance. Proven ability to lead client engagements and deliver high-quality data solutions that align with business objectives.

Highest-signal resume keywords
Microsoft AzureDatabricksData EngineeringPySparkDevOps for Data

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills
Data Platform DevelopmentBatch and Streaming Data IngestionData Transformation WorkflowsSQLSpark SQLDelta LakeData ModelingData GovernanceData WarehousingData Sharing
Soft Skills
Excellent Communication SkillsClient EngagementTeam CollaborationProblem SolvingAdaptability
Tools & Technologies
Microsoft FabricPower BIAzure Data FactorySynapse Data AnalyticsAzure SQLAzure Cosmos DBAKSDockerGitHubUnity Catalog
Certifications & Qualifications
Bachelor’s Degree in Computer Science or Related Field
Industry Keywords
Cloud Data SolutionsData ManagementData GovernanceMaster Data ManagementIndustry Security Requirements

Tech Stack

Tools & technologies
ApacheAzureCloudDockerPostgresPySparkPythonSparkSQLUnity

About the role

Key responsibilities & impact
  • Design, build, and optimize modern data platforms for clients using Microsoft Azure, Microsoft Fabric, Power BI, and Databricks
  • Work directly with clients to understand business goals, data challenges, and technical requirements
  • Lead or support discovery sessions, requirements workshops, architecture discussions, and solution reviews
  • Develop and optimize batch and streaming data ingestion pipelines from enterprise applications, databases, APIs, and file-based sources
  • Implement medallion/lakehouse architectures, dimensional models, and data transformation workflows for analytics and reporting
  • Engineer solutions using PySpark, Spark SQL, SQL, Python, Delta Lake, and orchestration tools within Azure and Databricks
  • Recommend best practices for data modeling, governance, lineage, monitoring, DevOps, and security
  • Contribute to solution architecture and deliver high-quality modern data solutions that drive measurable business value
  • Facilitate design sessions with client stakeholders and present recommendations to leadership teams

Requirements

What you’ll need
  • Bachelor’s degree in computer science or related field
  • 6+ years of experience in data engineering, data platform development, or cloud data solutions
  • 3+ years of hands-on experience with Azure Databricks, Apache Spark, or similar distributed data processing technologies
  • Expertise with Microsoft Azure infrastructure and data resources, including Fabric, Azure Data Factory, Synapse Data Analytics, Power BI, Azure SQL, Azure Cosmos DB, and Azure Database for PostgreSQL
  • Expertise with Databricks, including enterprise-level strategy and architecture with Unity Catalog, data warehousing, data sharing, and Mosaic AI
  • DevOps for data, GitHub, automated testing, and containers such as AKS, Docker, and registries
  • Excellent communication skills and ability to clearly explain concepts to teammates and customers
  • Ability to quickly learn new concepts and technologies
  • Preferred: experience working directly with clients, business stakeholders, or cross-functional teams in a consulting or professional services environment
  • Preferred: experience building data agents, including NLQ, Databricks Genie, and Fabric Data Agents
  • Preferred: experience with data management, governance, security, master data management, and industry security requirements
  • Preferred: broad experience with data/reporting tools, architectures, cloud vendors, and data/AI concepts beyond Microsoft

Benefits

Comp & perks
  • Equal opportunity employer commitment
  • Reasonable accommodation during the application or recruiting process for disabilities