Data Engineer

Lorven Technologies Inc

Charlotte, NC, United States

12 days ago

Role details

Contract type

Permanent contract

Employment type

Full-time (> 32 hours)

Experience level

Expert

Experience required

3 years minimum

Working hours

Regular working hours

Job source

www.dice.com

Tech stack

Query Performance Agile Methodology Artificial Intelligence Amazon Web Services Apache HTTP Server Microsoft Azure BigQuery Continuous Integration Data Architecture Information Engineering Data Governance Extract Transform Load (ETL)

+27 more

Data Security Data Systems Data Warehousing Python (Programming Language) Meta-Data Management Query Optimization Power BI SQL Databases Systems Integration Tableau (Software) Parquet Google Cloud Cloud Platform System Azure Data Factory Snowflake Generative AI Git Containerization Data Lakes Pyspark Kubernetes Qlikview Data Management Azure Synapse Analytics Data Pipelines Amazon Redshift Databricks

Job description

We are seeking an experienced Senior Data Engineer with strong Dremio expertise to design, build, and optimize modern data lakehouse solutions. The ideal candidate will have hands-on experience with Dremio, SQL, PySpark, cloud-based data platforms, and large-scale analytical environments. The role involves enabling high-performance data access, implementing data engineering pipelines, and supporting business intelligence and AI/ML workloads., * Design, develop, and maintain enterprise-scale data solutions using Dremio.
Build semantic datasets, virtual views, and optimized data models for analytics consumption.
Develop scalable ETL/ELT pipelines using Python, PySpark, and SQL.
Optimize query performance using Dremio Reflections and data partitioning strategies.
Collaborate with business analysts, data scientists, and BI teams to deliver trusted datasets.
Support data governance, lineage, security, and access control initiatives.
Troubleshoot production issues and perform root cause analysis.
Implement best practices for data quality, monitoring, and operational excellence.
Participate in architecture reviews and technology roadmap discussions.

Requirements

Must Have

8+ years of Data Engineering experience.
3+ years of hands-on experience with Dremio.
Strong SQL development and query optimization skills.
Experience with Python and PySpark.
Experience working with Data Lakes and Lakehouse architectures.
Knowledge of Apache Iceberg, Parquet, Arrow, Delta Lake, or similar technologies.
Experience with AWS, Azure, or Google Cloud Platform cloud platforms.
Strong understanding of Data Warehousing concepts.
Experience with Git, CI/CD pipelines, and Agile methodologies.

Preferred Experience with Snowflake, Databricks, Redshift, Synapse, or BigQuery. Experience integrating BI tools such as Power BI, Tableau, or Qlik. Familiarity with Data Governance and Metadata Management tools. Knowledge of Generative AI or AI-ready data platforms. Experience with Kubernetes and containerized deployments.

Nice to Have