Senior Data Engineer

Datavail

. Design, build and maintain production-grade batch, incremental, real-time and near-real-time data pipelines across Microsoft Fabric and Azure .

Posted 11/2/2026full-timeRemote • United StatesSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and maintaining data pipelines using Microsoft Fabric and Azure, with a strong focus on implementing advanced data engineering practices such as CDC, dimensional modeling, and CI/CD processes. Proficient in leveraging tools like PySpark, Spark SQL, and Delta Lake for data transformation and governance.

Highest-signal resume keywords

Data EngineeringAzure Solutions DeliveryAdvanced T-SQLDimensional ModelingCI/CD Automation

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data Pipeline DesignPySparkSpark SQLT-SQLDelta LakeCDC ImplementationDimensional ModelingData Vault 2.0Infrastructure as CodeDataOps

Soft Skills

Client CommunicationMentoringRisk Management

Tools & Technologies

Microsoft FabricAzure DevOpsGitHubPower BIData FactoryBicepTerraformPurviewReal-Time IntelligenceLakehouse

Certifications & Qualifications

DP-700DP-600DP-203

Industry Keywords

Data WarehousingStreamingEvent-DrivenGovernanceSecurity

Tech Stack

Tools & technologies

AzurePySparkPythonSparkSQLSSISTerraformVault

About the role

Key responsibilities & impact

Design, build and maintain production-grade batch, incremental, real-time and near-real-time data pipelines across Microsoft Fabric and Azure
Implement CDC, watermarking, merge/upsert, late-arriving-data and idempotent reprocessing patterns
Develop PySpark, Spark SQL and T-SQL transformations across bronze, silver and gold Delta Lake layers
Build Fabric solutions using OneLake, Lakehouse, Warehouse, Data Factory, Dataflows Gen2, Spark notebooks, Real-Time Intelligence and Power BI
Implement dimensional and Data Vault models, data-quality testing, reconciliation, observability, logging, alerting and SLA monitoring
Establish Git-based CI/CD and automated deployment using Azure DevOps or GitHub, Fabric deployment pipelines, REST APIs, Bicep and Terraform
Apply Purview catalog/lineage, least-privilege access, sensitivity controls, encryption and secure connectivity
Support migrations from SQL Server, SSIS, SSAS, legacy warehouses and Synapse to Fabric/Azure, including conversion, reconciliation and cutover
Prepare governed data for AI/ML and RAG workloads, including ingestion, chunking, embeddings, indexing and telemetry
Lead engineering workstreams, estimates, risk management, client communication, mentoring, reusable accelerators and operational handover

Requirements

What you’ll need

8+ years in data engineering/data warehousing
3+ years delivering Azure solutions and production
Microsoft Fabric experience
Advanced T-SQL, Spark SQL, Python/PySpark; working knowledge of KQL and DAX
Deep experience with Delta Lake, Spark tuning, medallion/lakehouse patterns, CDC and incremental loading
Strong dimensional modeling and working knowledge of Data Vault 2.0
Practical CI/CD, Git, automated testing, infrastructure as code, DataOps, governance and security experience
Professional-services/client-facing delivery experience
Authorization to work in the US and ability to travel up to 15%
Preferred: DP-700, DP-600, DP-203; streaming/event-driven, RAG/GenAI, Fabric IQ/data agents, and industry experience