FREE ACCESS
5,000–10,000 jobs/day
See all jobs on JobTailor
Search thousands of fresh jobs every day.
Discover
- Fresh listings
- Fast filters
- No subscription required
Create a free account and start exploring right away.
Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in designing and implementing Azure-based data architectures and ELT/ETL pipelines, with a strong focus on optimizing data ingestion, processing, and storage. Proficient in collaborating with data scientists to support machine learning initiatives and ensuring efficient data access for analytics.
Highest-signal resume keywords
Azure Data ArchitectureELT/ETL Pipeline DevelopmentSQL Database ManagementAzure Synapse AnalyticsPython and Pandas Development
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Data Architecture DesignPipeline OptimizationAdvanced SQL/T-SQL OperationsData ModelingData Ingestion and Processing
Tools & Technologies
Azure Data Lake StorageAzure Machine LearningSource Control SystemsData Validation FrameworksOperational Standards
Industry Keywords
Cloud-Based Data SolutionsFraud Detection InitiativesMachine Learning OperationsData Pipeline MonitoringStandard Operating Procedures
Tech Stack
Tools & technologiesAzureCloudETLPandasPythonSQL
About the role
Key responsibilities & impact- The Senior Data Engineer is responsible for designing, implementing, maintaining, and optimizing a cloud-based data architecture and data pipeline ecosystem.
- The position supports advanced analytics, machine learning operations, fraud detection initiatives, and investigative activities by delivering scalable, secure, and sustainable Azure-based data solutions.
- The Senior Data Engineer develops and maintains modern ELT/ETL pipelines, data models, source-controlled environments, and operational standards that enable efficient data ingestion, processing, storage, and access.
- Design, implement, and maintain scalable Azure-based data architecture supporting audits, investigations, and fraud analytics.
- Develop, optimize, and sustain ELT/ETL pipelines within Azure Synapse Analytics and Azure Machine Learning environments.
- Migrate and integrate large-scale datasets into Azure Data Lake Storage (ADLS).
- Establish source control, version management, and development standards across data engineering assets.
- Implement pipeline monitoring, validation, logging, and error-handling frameworks.
- Design and maintain data models, data dictionaries, entity relationship diagrams, and architectural documentation.
- Optimize ingestion, transformation, storage, and retrieval performance across diverse data sources and formats.
- Develop self-service data access capabilities for analysts and investigators.
- Collaborate with Data Scientists to ensure infrastructure effectively supports machine learning and AI initiatives.
- Author and maintain Standard Operating Procedures (SOPs) governing data pipeline development, deployment, and monitoring.
- Evaluate emerging AI-enabled engineering tools and LLM-assisted automation capabilities.
- Recommend and implement architectural improvements that increase efficiency, reliability, security, and cost effectiveness.
Requirements
What you’ll need- Bachelor's degree in Data Engineering, Computer Science, Data Science, Machine Learning, Mathematics, or related discipline; or 5 years of relevant applied experience.
- Five or more years of experience maintaining SQL database environments and performing advanced SQL/T-SQL operations.
- Five or more years of experience designing and maintaining cloud-based ELT/ETL solutions.
- Three or more years of experience working with Azure Synapse Analytics and Azure Machine Learning.
- Three or more years of experience developing data solutions using Python and Pandas.
- Experience supporting modern data platforms and cloud-native analytics architectures.
- Demonstrated expertise in data architecture design, pipeline optimization, and operational support.
Benefits
Comp & perks- Health insurance
- 401(k) matching
- Flexible work hours
- Paid time off
- Remote work options
