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Data Engineer
LHi Group LtdWoodbridge Township, NJ🇺🇸United StatesPosted 11 Aug 2026
Quick Overview
Salary
$88k - $105k/yr
Work Type
Hybrid
Level
Mid Senior
Job Description
Data Engineer | Metropark, New Jersey
Hybrid | $88,000-$105,000 Base + Bonus
We are seeking an early-career Data Engineer to join a growing technology team focused on developing and supporting modern data pipelines and cloud-based data infrastructure.
This opportunity is well suited to a Data Engineer, Data Analyst, or recent graduate with strong foundational skills in SQL and Python who is looking to build hands-on experience with Databricks, Apache Spark, PySpark, and modern lakehouse architecture.
Key Responsibilities
Required Qualifications
Preferred Qualifications
Compensation & Work Arrangement
Salary: $88,000-$105,000 base salary + discretionary bonus
Work Arrangement: Hybrid
This is an excellent opportunity for an early-career professional looking to develop a strong foundation in data engineering, cloud data platforms, Databricks, Spark, and lakehouse architecture while working alongside experienced engineers.
Interested in learning more? Apply directly or reach out to for additional information.
Data Engineer | Hybrid | Metropark, New Jersey
Hybrid | $88,000-$105,000 Base + Bonus
We are seeking an early-career Data Engineer to join a growing technology team focused on developing and supporting modern data pipelines and cloud-based data infrastructure.
This opportunity is well suited to a Data Engineer, Data Analyst, or recent graduate with strong foundational skills in SQL and Python who is looking to build hands-on experience with Databricks, Apache Spark, PySpark, and modern lakehouse architecture.
Key Responsibilities
- Support the development and maintenance of data pipelines across Bronze, Silver, and Gold medallion architecture layers
- Ingest and organize raw data within the Bronze layer
- Support data cleansing, deduplication, validation, and schema enforcement within the Silver layer
- Develop SQL and PySpark transformations based on defined business and technical requirements
- Assist with data quality, testing, monitoring, and troubleshooting of pipeline jobs
- Work with structured and semi-structured data within cloud-based data environments
- Collaborate closely with senior data engineers to learn and apply modern data engineering practices
- Contribute to scalable and reliable data solutions using version-controlled development practices
Required Qualifications
- 0-2 years of experience in Data Engineering, Analytics, Computer Science, or a related field; internships and academic projects are considered
- Foundational knowledge of SQL, including joins, filtering, aggregations, and querying relational data
- Experience with Python and an understanding of basic object-oriented programming concepts
- Understanding of core data concepts, including tables, schemas, relational databases, and data structures
- Familiarity with Git or demonstrated ability to quickly learn version-control practices
- Strong interest in developing expertise across Databricks, Spark, and cloud technologies
- Strong analytical, problem-solving, and communication skills
Preferred Qualifications
- Exposure to Databricks, Apache Spark, or PySpark
- Understanding of Delta Lake or medallion architecture
- Experience with Azure, AWS, or Google Cloud Platform
- Databricks certification
- Exposure to BI, reporting, or data visualization tools
- Academic or project experience building data pipelines or working with data transformation workflows
Compensation & Work Arrangement
Salary: $88,000-$105,000 base salary + discretionary bonus
Work Arrangement: Hybrid
This is an excellent opportunity for an early-career professional looking to develop a strong foundation in data engineering, cloud data platforms, Databricks, Spark, and lakehouse architecture while working alongside experienced engineers.
Interested in learning more? Apply directly or reach out to for additional information.
Data Engineer | Hybrid | Metropark, New Jersey
Skills
SQL
AWS
Apache
Apache Spark
Azure
Databricks
Git
Google Cloud
Python
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