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Mid LevelFull-timePythonAWSMachine LearningData ScienceAIML
Salary Range
$102,000 - $138,000 /year
This salary is estimated based on similar roles. The actual salary may vary.
About the Role
We are looking for a Data Engineer to join our team at MetroStar. This role involves designing and maintaining scalable data pipelines and cloud-based data platforms that support advanced analytics and machine learning workloads.
Key Responsibilities
- →Design and implement data ingestion, transformation, and enrichment pipelines across multiple concurrent projects with varying data modalities
- →Develop and manage cloud-native data services including object storage workflows, vector database integration, and structured data warehousing
- →Work closely with AI/ML engineers to operationalize data pipelines that feed training, inference, and retrieval-augmented generation workloads
- →Establish data quality, lineage, and governance practices across projects
- →Support the processing and organization of unstructured data into formats suitable for embedding generation, semantic search, and summarization
- →Present technical approaches and data architecture decisions to both technical teammates and non-technical stakeholders
Requirements
- ✓Bachelor's Degree in Computer Science, Data Science, Information Systems, Engineering, or a comparable technical discipline
- ✓An active Secret clearance or the ability to obtain
- ✓2-4+ years of professional experience in data engineering, data platform development, or a closely related technical role
- ✓Strong proficiency in Python for data engineering
- ✓Experience designing and building ETL/ELT pipelines for structured and semi-structured data in cloud environments
- ✓Experience with AWS cloud services for data workflows
- ✓Hands-on experience with at least one distributed data processing framework
- ✓Demonstrated ability to work with diverse data modalities
- ✓Experience with SQL and data warehousing concepts
- ✓Strong experience with data pipeline orchestration, scheduling, and monitoring in production environments
- ✓Experience building data pipelines that ingest, transform, or serve data through RESTful APIs
- ✓Strong communication skills with the ability to explain data architecture decisions
Benefits
- ★Health, dental, and vision insurance
- ★401(k) retirement plan with company match
- ★Paid time off (PTO) and holidays
- ★Parental Leave and dependent care
- ★Flexible work arrangements
- ★Professional development opportunities
- ★Employee assistance and wellness programs
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