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LG
LHi Group Ltd
Data Engineer
Entry-Level JobVerifiedNo experience needed
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Based on New Jersey data
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What they do
A Data Engineer designs, builds and manages the information or big data infrastructure. Develops the architecture that helps analyze and process data in the way the organization needs it. Makes sure those systems are performing smoothly.
$116,216 / year median in New Jersey
+11% projected growth
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 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