Overview
Hybrid
Depends on Experience
Full Time
Skills
Data Warehousing
Snowflake
AWS
DBT
Informatica
Python
SSIS
ETL
Data Lake
Azure Data Factory
AWS Glue
Scala
Ggit
CI/CD
Job Details
Job Title: Data Engineer
Location: Princeton, NJ (Hybrid/On-site)
Type of Employment: Full-time
About the Role:
We are seeking a highly skilled Data Engineer with 5–7 years of experience to design, develop, and optimize data pipelines, ETL processes, and cloud-based data platforms. The ideal candidate has strong problem-solving abilities, hands-on experience with modern data engineering tools, and a solid understanding of data architecture and analytics workflows.
Key Responsibilities:
- Design, build, and maintain scalable ETL pipelines, data ingestion processes, and data transformation workflows.
- Develop and manage Data Lakes, Data Warehouses, and cloud-based data platforms.
- Work with platforms such as Azure Data Factory, AWS Glue, or similar orchestration tools to automate data workflows.
- Build, optimize, and maintain SQL queries, stored procedures, and database structures.
- Collaborate with data scientists, analysts, and business stakeholders to deliver reliable, high-quality datasets.
- Ensure data quality, integrity, and security across multiple systems and environments.
- Implement best practices for data governance, metadata management, and data cataloging.
- Monitor and troubleshoot data pipelines to ensure high availability and performance.
- Participate in Agile ceremonies, code reviews, and continuous improvement initiatives.
Required Qualifications:
- 5–7 years of hands-on experience as a Data Engineer or similar role.
- Strong proficiency in ETL development, data integration, and pipeline orchestration.
- Experience with Data Lakes, Data Warehouses, and distributed data processing.
- Hands-on experience with Azure Data Factory, AWS Glue, or equivalent tools.
- Strong SQL skills with the ability to write complex queries and optimize performance.
- Experience with Python or Scala for data processing tasks.
- Familiarity with cloud platforms (Azure, AWS, or Google Cloud Platform) and data storage solutions.
- Experience with version control tools (Git) and CI/CD pipelines.
- Understanding of data modeling (dimensional, relational) and BI concepts.
Preferred Skills:
- Experience with Big Data technologies (Spark, Databricks, Hadoop).
- Knowledge of Azure Synapse, Snowflake, Redshift, or BigQuery.
- Background in API integrations, streaming technologies (Kafka, EventHub), or real-time data pipelines.
- Experience with data quality frameworks and monitoring tools.
- Understanding of security and compliance standards (PII, HIPAA, GDPR).
Education:
Bachelor’s degree in Computer Science, Information Systems, Data Engineering, or a related field (or equivalent experience).
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